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apache/iotdb/refs/heads/fixDeviceEntryConf/./iotdb-client/client-py/tests/integration/test_treemodel_insert.py
blob: 9feda17133f9e33bd5de74c05aeb1788a66e98a9 [file]
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
#
import numpy as np
from .iotdb_container import IoTDBContainer
from iotdb.Session import Session
from iotdb.utils.Tablet import Tablet
from datetime import date
from iotdb.utils.BitMap import BitMap
from iotdb.utils.IoTDBConstants import TSDataType, TSEncoding, Compressor
from iotdb.utils.NumpyTablet import NumpyTablet
# Test writing a tablet data to a non aligned time series
def test_insert_tablet():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test1.g1")
ts_path_lst = [
"root.test1.g1.d1.BOOLEAN",
"root.test1.g1.d1.INT32",
"root.test1.g1.d1.INT64",
"root.test1.g1.d1.FLOAT",
"root.test1.g1.d1.DOUBLE",
"root.test1.g1.d1.TEXT",
"root.test1.g1.d1.TS",
"root.test1.g1.d1.DATE",
"root.test1.g1.d1.BLOB",
"root.test1.g1.d1.STRING",
"root.test1.g1.d2.BOOLEAN",
"root.test1.g1.d2.INT32",
"root.test1.g1.d2.INT64",
"root.test1.g1.d2.FLOAT",
"root.test1.g1.d2.DOUBLE",
"root.test1.g1.d2.TEXT",
"root.test1.g1.d2.TS",
"root.test1.g1.d2.DATE",
"root.test1.g1.d2.BLOB",
"root.test1.g1.d2.STRING",
"root.test1.g1.d3.BOOLEAN",
"root.test1.g1.d3.INT32",
"root.test1.g1.d3.INT64",
"root.test1.g1.d3.FLOAT",
"root.test1.g1.d3.DOUBLE",
"root.test1.g1.d3.TEXT",
"root.test1.g1.d3.TS",
"root.test1.g1.d3.DATE",
"root.test1.g1.d3.BLOB",
"root.test1.g1.d3.STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_multi_time_series(
ts_path_lst,
data_type_lst,
encoding_lst,
compressor_lst,
props_lst=None,
tags_lst=None,
attributes_lst=None,
alias_lst=None,
)
# 1、Inserting tablet data
expect = 10
device_id = "root.test1.g1.d1"
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
values_ = [
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test101",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
None,
None,
None,
None,
None,
"",
None,
date(1970, 1, 1),
"".encode("utf-8"),
"",
],
[
True,
-0,
-0,
-0.0,
-0.0,
" ",
11,
date(1970, 1, 1),
" ".encode("utf-8"),
" ",
],
[
True,
10,
11,
1.1,
10011.1,
"test101",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
]
timestamps_ = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
tablet_ = Tablet(device_id, measurements_, data_types_, values_, timestamps_)
session.insert_tablet(tablet_)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test1.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
# 2、Inserting Numpy Tablet data (No null)
expect = 10
device_id = "root.test1.g1.d2"
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, True],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test101",
"test101",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test101",
"test101",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
np_tablet_ = NumpyTablet(
device_id, measurements_, data_types_, np_values_, np_timestamps_
)
session.insert_tablet(np_tablet_)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test1.g1.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
# 3、Inserting Numpy Tablet data (Contains null)
expect = 10
device_id = "root.test1.g1.d3"
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, False],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
np_bitmaps_ = []
for i in range(len(measurements_)):
np_bitmaps_.append(BitMap(len(np_timestamps_)))
np_bitmaps_[0].mark(9)
np_bitmaps_[1].mark(8)
np_bitmaps_[2].mark(9)
np_bitmaps_[4].mark(8)
np_bitmaps_[5].mark(9)
np_bitmaps_[6].mark(8)
np_bitmaps_[7].mark(9)
np_bitmaps_[8].mark(8)
np_bitmaps_[9].mark(9)
np_tablet_ = NumpyTablet(
device_id,
measurements_,
data_types_,
np_values_,
np_timestamps_,
np_bitmaps_,
)
session.insert_tablet(np_tablet_)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test1.g1.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writing a tablet data to align the time series
def test_insert_aligned_tablet():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test2.g3")
device_id = "root.test2.g3.d1"
measurements_lst = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_aligned_time_series(
device_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device_id = "root.test2.g3.d2"
measurements_lst = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_aligned_time_series(
device_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device_id = "root.test2.g3.d3"
measurements_lst = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_aligned_time_series(
device_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
# 1、Inserting tablet data
expect = 10
device_id = "root.test2.g3.d1"
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
values_ = [
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
None,
None,
None,
None,
None,
"",
None,
date(1970, 1, 1),
"".encode("utf-8"),
"",
],
[
True,
-0,
-0,
-0.0,
-0.0,
" ",
11,
date(1970, 1, 1),
" ".encode("utf-8"),
" ",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
]
timestamps_ = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
tablet_ = Tablet(device_id, measurements_, data_types_, values_, timestamps_)
session.insert_aligned_tablet(tablet_)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test2.g3.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
# 2、Inserting Numpy Tablet data (No null)
expect = 10
device_id = "root.test2.g3.d2"
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, True],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
np_tablet_ = NumpyTablet(
device_id, measurements_, data_types_, np_values_, np_timestamps_
)
session.insert_aligned_tablet(np_tablet_)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test2.g3.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
# 3、Inserting Numpy Tablet data (Contains null)
expect = 10
device_id = "root.test2.g3.d3"
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, False],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
np_bitmaps_ = []
for i in range(len(measurements_)):
np_bitmaps_.append(BitMap(len(np_timestamps_)))
np_bitmaps_[0].mark(9)
np_bitmaps_[1].mark(8)
np_bitmaps_[2].mark(9)
np_bitmaps_[4].mark(8)
np_bitmaps_[5].mark(9)
np_bitmaps_[6].mark(8)
np_bitmaps_[7].mark(9)
np_bitmaps_[8].mark(8)
np_bitmaps_[9].mark(9)
np_tablet_ = NumpyTablet(
device_id,
measurements_,
data_types_,
np_values_,
np_timestamps_,
np_bitmaps_,
)
session.insert_aligned_tablet(np_tablet_)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test2.g3.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writing multiple tablet data to non aligned time series
def test_insert_tablets():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test3.g1")
session.set_storage_group("root.test3.g2")
ts_path_lst = [
"root.test3.g1.d1.BOOLEAN",
"root.test3.g1.d1.INT32",
"root.test3.g1.d1.INT64",
"root.test3.g1.d1.FLOAT",
"root.test3.g1.d1.DOUBLE",
"root.test3.g1.d1.TEXT",
"root.test3.g1.d1.TS",
"root.test3.g1.d1.DATE",
"root.test3.g1.d1.BLOB",
"root.test3.g1.d1.STRING",
"root.test3.g1.d2.BOOLEAN",
"root.test3.g1.d2.INT32",
"root.test3.g1.d2.INT64",
"root.test3.g1.d2.FLOAT",
"root.test3.g1.d2.DOUBLE",
"root.test3.g1.d2.TEXT",
"root.test3.g1.d2.TS",
"root.test3.g1.d2.DATE",
"root.test3.g1.d2.BLOB",
"root.test3.g1.d2.STRING",
"root.test3.g1.d3.BOOLEAN",
"root.test3.g1.d3.INT32",
"root.test3.g1.d3.INT64",
"root.test3.g1.d3.FLOAT",
"root.test3.g1.d3.DOUBLE",
"root.test3.g1.d3.TEXT",
"root.test3.g1.d3.TS",
"root.test3.g1.d3.DATE",
"root.test3.g1.d3.BLOB",
"root.test3.g1.d3.STRING",
"root.test3.g2.d1.BOOLEAN",
"root.test3.g2.d1.INT32",
"root.test3.g2.d1.INT64",
"root.test3.g2.d1.FLOAT",
"root.test3.g2.d1.DOUBLE",
"root.test3.g2.d1.TEXT",
"root.test3.g2.d1.TS",
"root.test3.g2.d1.DATE",
"root.test3.g2.d1.BLOB",
"root.test3.g2.d1.STRING",
"root.test3.g2.d2.BOOLEAN",
"root.test3.g2.d2.INT32",
"root.test3.g2.d2.INT64",
"root.test3.g2.d2.FLOAT",
"root.test3.g2.d2.DOUBLE",
"root.test3.g2.d2.TEXT",
"root.test3.g2.d2.TS",
"root.test3.g2.d2.DATE",
"root.test3.g2.d2.BLOB",
"root.test3.g2.d2.STRING",
"root.test3.g2.d3.BOOLEAN",
"root.test3.g2.d3.INT32",
"root.test3.g2.d3.INT64",
"root.test3.g2.d3.FLOAT",
"root.test3.g2.d3.DOUBLE",
"root.test3.g2.d3.TEXT",
"root.test3.g2.d3.TS",
"root.test3.g2.d3.DATE",
"root.test3.g2.d3.BLOB",
"root.test3.g2.d3.STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_multi_time_series(
ts_path_lst,
data_type_lst,
encoding_lst,
compressor_lst,
props_lst=None,
tags_lst=None,
attributes_lst=None,
alias_lst=None,
)
# 1、Inserting tablet data
expect = 30
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
values_ = [
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
None,
None,
None,
None,
None,
"",
None,
date(1970, 1, 1),
"".encode("utf-8"),
"",
],
[
True,
-0,
-0,
-0.0,
-0.0,
" ",
11,
date(1970, 1, 1),
" ".encode("utf-8"),
" ",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
]
timestamps_ = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
device1_id = "root.test3.g1.d1"
device2_id = "root.test3.g1.d2"
device3_id = "root.test3.g1.d3"
tablet1_ = Tablet(device1_id, measurements_, data_types, values_, timestamps_)
tablet2_ = Tablet(device2_id, measurements_, data_types, values_, timestamps_)
tablet3_ = Tablet(device3_id, measurements_, data_types, values_, timestamps_)
tablet_lst = [tablet1_, tablet2_, tablet3_]
session.insert_tablets(tablet_lst)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test3.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test3.g1.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test3.g1.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
# 2、Inserting Numpy Tablet data
expect = 30
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, True],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
device1_id = "root.test3.g2.d1"
device2_id = "root.test3.g2.d2"
device3_id = "root.test3.g2.d3"
np_tablet1_ = NumpyTablet(
device1_id, measurements_, data_types_, np_values_, np_timestamps_
)
np_tablet2_ = NumpyTablet(
device2_id, measurements_, data_types_, np_values_, np_timestamps_
)
np_tablet3_ = NumpyTablet(
device3_id, measurements_, data_types_, np_values_, np_timestamps_
)
np_tablet_list = [np_tablet1_, np_tablet2_, np_tablet3_]
session.insert_tablets(np_tablet_list)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test3.g2.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test3.g2.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test3.g2.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writing multiple tablet data to aligned time series
def test_insert_aligned_tablets():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test4.g1")
session.set_storage_group("root.test4.g2")
measurements_lst = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
device11_id = "root.test4.g1.d1"
session.create_aligned_time_series(
device11_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device12_id = "root.test4.g1.d2"
session.create_aligned_time_series(
device12_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device13_id = "root.test4.g1.d3"
session.create_aligned_time_series(
device13_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device21_id = "root.test4.g2.d1"
session.create_aligned_time_series(
device21_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device22_id = "root.test4.g2.d2"
session.create_aligned_time_series(
device22_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device23_id = "root.test4.g2.d3"
session.create_aligned_time_series(
device23_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
# 1、Inserting tablet data
expect = 30
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
values_ = [
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
None,
None,
None,
None,
None,
"",
None,
date(1970, 1, 1),
"".encode("utf-8"),
"",
],
[
True,
-0,
-0,
-0.0,
-0.0,
" ",
11,
date(1970, 1, 1),
" ".encode("utf-8"),
" ",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
]
timestamps_ = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
device1_id = "root.test4.g1.d1"
device2_id = "root.test4.g1.d2"
device3_id = "root.test4.g1.d3"
tablet1_ = Tablet(device1_id, measurements_, data_types, values_, timestamps_)
tablet2_ = Tablet(device2_id, measurements_, data_types, values_, timestamps_)
tablet3_ = Tablet(device3_id, measurements_, data_types, values_, timestamps_)
tablet_lst = [tablet1_, tablet2_, tablet3_]
session.insert_aligned_tablets(tablet_lst)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test4.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test4.g1.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test4.g1.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
# 2、Inserting Numpy Tablet data
expect = 30
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, True],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
device1_id = "root.test4.g2.d1"
device2_id = "root.test4.g2.d2"
device_id = "root.test4.g2.d3"
np_tablet1_ = NumpyTablet(
device1_id, measurements_, data_types_, np_values_, np_timestamps_
)
np_tablet2_ = NumpyTablet(
device2_id, measurements_, data_types_, np_values_, np_timestamps_
)
np_tablet3_ = NumpyTablet(
device_id, measurements_, data_types_, np_values_, np_timestamps_
)
np_tablet_list = [np_tablet1_, np_tablet2_, np_tablet3_]
session.insert_aligned_tablets(np_tablet_list)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test4.g2.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test4.g2.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test4.g2.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writing a Record data to a non aligned time series
def test_insert_record():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test5.g1")
ts_path_lst = [
"root.test5.g1.d1.BOOLEAN",
"root.test5.g1.d1.INT32",
"root.test5.g1.d1.INT64",
"root.test5.g1.d1.FLOAT",
"root.test5.g1.d1.DOUBLE",
"root.test5.g1.d1.TEXT",
"root.test5.g1.d1.TS",
"root.test5.g1.d1.DATE",
"root.test5.g1.d1.BLOB",
"root.test5.g1.d1.STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_multi_time_series(
ts_path_lst,
data_type_lst,
encoding_lst,
compressor_lst,
props_lst=None,
tags_lst=None,
attributes_lst=None,
alias_lst=None,
)
expect = 9
session.insert_record(
"root.test5.g1.d1",
1,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
)
session.insert_record(
"root.test5.g1.d1",
2,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
)
session.insert_record(
"root.test5.g1.d1",
3,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
)
session.insert_record(
"root.test5.g1.d1",
4,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
)
session.insert_record(
"root.test5.g1.d1",
5,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
)
session.insert_record(
"root.test5.g1.d1",
6,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
)
session.insert_record(
"root.test5.g1.d1",
7,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
)
session.insert_record(
"root.test5.g1.d1",
9,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-0,
-0,
-0.0,
-0.0,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
)
session.insert_record(
"root.test5.g1.d1",
10,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test5.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writing a Record data to align the time series
def test_insert_aligned_record():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test6.g1")
measurements_lst = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
device11_id = "root.test6.g1.d1"
session.create_aligned_time_series(
device11_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
expect = 9
session.insert_aligned_record(
"root.test6.g1.d1",
1,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
2,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
3,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
4,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
5,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
6,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
7,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
9,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
-0,
-0,
-0.0,
-0.0,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
)
session.insert_aligned_record(
"root.test6.g1.d1",
10,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test6.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writing multiple Record data to non aligned time series
def test_insert_records():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test7.g1")
ts_path_lst = [
"root.test7.g1.d1.BOOLEAN",
"root.test7.g1.d1.INT32",
"root.test7.g1.d1.INT64",
"root.test7.g1.d1.FLOAT",
"root.test7.g1.d1.DOUBLE",
"root.test7.g1.d1.TEXT",
"root.test7.g1.d1.TS",
"root.test7.g1.d1.DATE",
"root.test7.g1.d1.BLOB",
"root.test7.g1.d1.STRING",
"root.test7.g1.d2.BOOLEAN",
"root.test7.g1.d2.INT32",
"root.test7.g1.d2.INT64",
"root.test7.g1.d2.FLOAT",
"root.test7.g1.d2.DOUBLE",
"root.test7.g1.d2.TEXT",
"root.test7.g1.d2.TS",
"root.test7.g1.d2.DATE",
"root.test7.g1.d2.BLOB",
"root.test7.g1.d2.STRING",
"root.test7.g1.d3.BOOLEAN",
"root.test7.g1.d3.INT32",
"root.test7.g1.d3.INT64",
"root.test7.g1.d3.FLOAT",
"root.test7.g1.d3.DOUBLE",
"root.test7.g1.d3.TEXT",
"root.test7.g1.d3.TS",
"root.test7.g1.d3.DATE",
"root.test7.g1.d3.BLOB",
"root.test7.g1.d3.STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_multi_time_series(
ts_path_lst,
data_type_lst,
encoding_lst,
compressor_lst,
props_lst=None,
tags_lst=None,
attributes_lst=None,
alias_lst=None,
)
expect = 9
session.insert_records(
[
"root.test7.g1.d1",
"root.test7.g1.d2",
"root.test7.g1.d3",
"root.test7.g1.d1",
"root.test7.g1.d2",
"root.test7.g1.d3",
"root.test7.g1.d1",
"root.test7.g1.d2",
"root.test7.g1.d3",
],
[1, 2, 3, 4, 5, 6, 7, 8, 9],
[
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
],
[
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
],
[
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
-0,
-0,
-0.0,
-0.0,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
],
)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test7.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test7.g1.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test7.g1.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writing multiple Record data to aligned time series
def test_insert_aligned_records():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test8.g1")
measurements_lst = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
device11_id = "root.test8.g1.d1"
session.create_aligned_time_series(
device11_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device11_id = "root.test8.g1.d2"
session.create_aligned_time_series(
device11_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
device11_id = "root.test8.g1.d3"
session.create_aligned_time_series(
device11_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
expect = 9
session.insert_aligned_records(
[
"root.test8.g1.d1",
"root.test8.g1.d2",
"root.test8.g1.d3",
"root.test8.g1.d1",
"root.test8.g1.d2",
"root.test8.g1.d3",
"root.test8.g1.d1",
"root.test8.g1.d2",
"root.test8.g1.d3",
],
[1, 2, 3, 4, 5, 6, 7, 8, 9],
[
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
],
[
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
],
[
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
-0,
-0,
-0.0,
-0.0,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
],
)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test8.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test8.g1.d2"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
with session.execute_query_statement(
"select * from root.test8.g1.d3"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test inserting multiple Record data belonging to the same non aligned device
def test_insert_records_of_one_device():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test9.g1")
ts_path_lst = [
"root.test9.g1.d1.BOOLEAN",
"root.test9.g1.d1.INT32",
"root.test9.g1.d1.INT64",
"root.test9.g1.d1.FLOAT",
"root.test9.g1.d1.DOUBLE",
"root.test9.g1.d1.TEXT",
"root.test9.g1.d1.TS",
"root.test9.g1.d1.DATE",
"root.test9.g1.d1.BLOB",
"root.test9.g1.d1.STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_multi_time_series(
ts_path_lst,
data_type_lst,
encoding_lst,
compressor_lst,
props_lst=None,
tags_lst=None,
attributes_lst=None,
alias_lst=None,
)
expect = 9
session.insert_records_of_one_device(
"root.test9.g1.d1",
[1, 2, 3, 4, 5, 6, 7, 8, 9],
[
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
],
[
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
],
[
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
-0,
-0,
-0.0,
-0.0,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
],
)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test9.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test inserting multiple Record data belonging to the same aligned device
def test_insert_aligned_records_of_one_device():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test10.g1")
measurements_lst = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_type_lst = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
encoding_lst = [
TSEncoding.RLE,
TSEncoding.CHIMP,
TSEncoding.ZIGZAG,
TSEncoding.RLBE,
TSEncoding.SPRINTZ,
TSEncoding.DICTIONARY,
TSEncoding.TS_2DIFF,
TSEncoding.CHIMP,
TSEncoding.PLAIN,
TSEncoding.DICTIONARY,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
device11_id = "root.test10.g1.d1"
session.create_aligned_time_series(
device11_id, measurements_lst, data_type_lst, encoding_lst, compressor_lst
)
expect = 9
session.insert_aligned_records_of_one_device(
"root.test10.g1.d1",
[1, 2, 3, 4, 5, 6, 7, 8, 9],
[
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
],
[
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
[
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
],
],
[
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
-0,
-0,
-0.0,
-0.0,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
],
)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test10.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test writes with type inference
def test_insert_str_record():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
# Preparation before testing
session.set_storage_group("root.test11.g1")
ts_path_lst = [
"root.test9.g1.d1.BOOLEAN",
"root.test9.g1.d1.INT32",
"root.test9.g1.d1.INT64",
"root.test9.g1.d1.FLOAT",
"root.test9.g1.d1.DOUBLE",
"root.test9.g1.d1.TEXT",
"root.test9.g1.d1.TS",
"root.test9.g1.d1.DATE",
"root.test9.g1.d1.BLOB",
"root.test9.g1.d1.STRING",
]
data_type_lst = [
TSDataType.TEXT,
TSDataType.DOUBLE,
TSDataType.DOUBLE,
TSDataType.DOUBLE,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TEXT,
TSDataType.TEXT,
]
encoding_lst = [
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
TSEncoding.PLAIN,
]
compressor_lst = [
Compressor.UNCOMPRESSED,
Compressor.SNAPPY,
Compressor.LZ4,
Compressor.GZIP,
Compressor.ZSTD,
Compressor.LZMA2,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
Compressor.GZIP,
]
session.create_multi_time_series(
ts_path_lst,
data_type_lst,
encoding_lst,
compressor_lst,
props_lst=None,
tags_lst=None,
attributes_lst=None,
alias_lst=None,
)
expect = 1
session.insert_str_record(
"root.test11.g1.d1",
1,
[
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
],
[
"true",
"10",
"11",
"11.11",
"10011.1",
"test01",
"11",
"1970-01-01",
'b"x12x34"',
"string01",
],
)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement(
"select * from root.test11.g1.d1"
) as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()
# Test automatic create
def test_insert_auto_create():
with IoTDBContainer("iotdb:dev") as db:
db: IoTDBContainer
session = Session(db.get_container_host_ip(), db.get_exposed_port(6667))
session.open()
expect = 360
# Test non aligned tablet writing
num = 0
for i in range(1, 10):
device_id = "root.repeat.g1.fd_a" + str(num)
num = num + 1
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
values_ = [
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
None,
None,
None,
None,
None,
"",
None,
date(1970, 1, 1),
"".encode("utf-8"),
"",
],
[
True,
-0,
-0,
-0.0,
-0.0,
" ",
11,
date(1970, 1, 1),
" ".encode("utf-8"),
" ",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
]
timestamps_ = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
tablet_ = Tablet(
device_id, measurements_, data_types_, values_, timestamps_
)
session.insert_tablet(tablet_)
# Test non aligned numpy tablet writing
num = 0
for i in range(1, 10):
device_id = "root.repeat.g1.fd_b" + str(num)
num = num + 1
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, True],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
np_tablet_ = NumpyTablet(
device_id, measurements_, data_types_, np_values_, np_timestamps_
)
session.insert_tablet(np_tablet_)
# Test aligning tablet writing
num = 0
for i in range(1, 10):
device_id = "root.repeat.g1.d_c" + str(num)
num = num + 1
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
values_ = [
[
False,
0,
0,
0.0,
0.0,
"1234567890",
0,
date(1970, 1, 1),
"1234567890".encode("utf-8"),
"1234567890",
],
[
True,
-2147483648,
-9223372036854775808,
-0.12345678,
-0.12345678901234567,
"abcdefghijklmnopqrstuvwsyz",
-9223372036854775808,
date(1000, 1, 1),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz",
],
[
True,
2147483647,
9223372036854775807,
0.123456789,
0.12345678901234567,
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
9223372036854775807,
date(9999, 12, 31),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~",
],
[
True,
1,
1,
1.0,
1.0,
"没问题",
1,
date(1970, 1, 1),
"没问题".encode("utf-8"),
"没问题",
],
[
True,
-1,
-1,
1.1234567,
1.1234567890123456,
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
11,
date(1970, 1, 1),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
],
[
True,
10,
11,
4.123456,
4.123456789012345,
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
11,
date(1970, 1, 1),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
],
[
True,
-10,
-11,
12.12345,
12.12345678901234,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
[
None,
None,
None,
None,
None,
"",
None,
date(1970, 1, 1),
"".encode("utf-8"),
"",
],
[
True,
-0,
-0,
-0.0,
-0.0,
" ",
11,
date(1970, 1, 1),
" ".encode("utf-8"),
" ",
],
[
True,
10,
11,
1.1,
10011.1,
"test01",
11,
date(1970, 1, 1),
"Hello, World!".encode("utf-8"),
"string01",
],
]
timestamps_ = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
tablet_ = Tablet(
device_id, measurements_, data_types_, values_, timestamps_
)
session.insert_aligned_tablet(tablet_)
# Test alignment of numpy tablet writing
num = 0
for i in range(1, 10):
device_id = "root.repeat.g1.d_d" + str(num)
num = num + 1
measurements_ = [
"BOOLEAN",
"INT32",
"INT64",
"FLOAT",
"DOUBLE",
"TEXT",
"TS",
"DATE",
"BLOB",
"STRING",
]
data_types_ = [
TSDataType.BOOLEAN,
TSDataType.INT32,
TSDataType.INT64,
TSDataType.FLOAT,
TSDataType.DOUBLE,
TSDataType.TEXT,
TSDataType.TIMESTAMP,
TSDataType.DATE,
TSDataType.BLOB,
TSDataType.STRING,
]
np_values_ = [
np.array(
[False, True, False, True, False, True, False, True, False, True],
TSDataType.BOOLEAN.np_dtype(),
),
np.array(
[0, -2147483648, 2147483647, 1, -1, 10, -10, -0, 10, 10],
TSDataType.INT32.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.INT64.np_dtype(),
),
np.array(
[
0.0,
-0.12345678,
0.123456789,
1.0,
1.1234567,
4.123456,
12.12345,
-0.0,
1.1,
1.1,
],
TSDataType.FLOAT.np_dtype(),
),
np.array(
[
0.0,
-0.12345678901234567,
0.12345678901234567,
1.0,
1.1234567890123456,
4.123456789012345,
12.12345678901234,
-0.0,
1.1,
1.1,
],
TSDataType.DOUBLE.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.TEXT.np_dtype(),
),
np.array(
[
0,
-9223372036854775808,
9223372036854775807,
1,
-1,
10,
-10,
-0,
10,
10,
],
TSDataType.TIMESTAMP.np_dtype(),
),
np.array(
[
date(1970, 1, 1),
date(1000, 1, 1),
date(9999, 12, 31),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
date(1970, 1, 1),
],
TSDataType.DATE.np_dtype(),
),
np.array(
[
"1234567890".encode("utf-8"),
"abcdefghijklmnopqrstuvwsyz".encode("utf-8"),
"!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"),
"没问题".encode("utf-8"),
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"),
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode(
"utf-8"
),
"".encode("utf-8"),
" ".encode("utf-8"),
"1234567890".encode("utf-8"),
"1234567890".encode("utf-8"),
],
TSDataType.BLOB.np_dtype(),
),
np.array(
[
"1234567890",
"abcdefghijklmnopqrstuvwsyz",
"!@#$%^&*()_+}{|:'`~-=[];,./<>?~",
"没问题",
"！@#￥%……&*（）——|：“《》？·【】、；‘，。/",
"1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题",
"",
" ",
"test01",
"test01",
],
TSDataType.STRING.np_dtype(),
),
]
np_timestamps_ = np.array(
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], TSDataType.INT64.np_dtype()
)
np_tablet_ = NumpyTablet(
device_id, measurements_, data_types_, np_values_, np_timestamps_
)
session.insert_aligned_tablet(np_tablet_)
# Calculate the number of rows in the actual time series
actual = 0
with session.execute_query_statement("show timeseries") as session_data_set:
session_data_set.set_fetch_size(1024)
while session_data_set.has_next():
print(session_data_set.next())
actual = actual + 1
# Determine whether it meets expectations
assert expect == actual
session.close()