| # 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 datetime import date |
| from iotdb.Session import Session |
| from iotdb.utils.BitMap import BitMap |
| from iotdb.utils.IoTDBConstants import TSDataType |
| from iotdb.utils.Tablet import Tablet, ColumnType |
| from iotdb.utils.NumpyTablet import NumpyTablet |
| from datetime import date |
| from iotdb.IoTDBContainer import IoTDBContainer |
| |
| |
| # Test inserting tablet data |
| def test_insert_relational_tablet_use_tablet(): |
| with IoTDBContainer("iotdb:dev") as db: |
| db: IoTDBContainer |
| session = Session( |
| db.get_container_host_ip(), db.get_exposed_port(6667), sql_dialect="table" |
| ) |
| session.open() |
| |
| # Preparation before testing |
| session.execute_non_query_statement( |
| "create database test_insert_relational_tablet_tablet" |
| ) |
| session.execute_non_query_statement("use test_insert_relational_tablet_tablet") |
| session.execute_non_query_statement( |
| "create table table_a(" |
| '"地区" STRING ID, "厂号" STRING ID, "设备号" STRING ID, ' |
| '"日期" string attribute, "时间" string attribute, "负责人" string attribute,' |
| '"测点1" BOOLEAN MEASUREMENT, "测点2" INT32 MEASUREMENT, "测点3" INT64 MEASUREMENT, "测点4" FLOAT MEASUREMENT, "测点5" DOUBLE MEASUREMENT,' |
| '"测点6" TEXT MEASUREMENT, "测点7" TIMESTAMP MEASUREMENT, "测点8" DATE MEASUREMENT, "测点9" BLOB MEASUREMENT, "测点10" STRING MEASUREMENT)' |
| ) |
| session.execute_non_query_statement( |
| "create table table_b(" |
| "id1 STRING ID, id2 STRING ID, id3 STRING ID, " |
| "attr1 string attribute, attr2 string attribute, attr3 string attribute," |
| "BOOLEAN BOOLEAN MEASUREMENT, INT32 INT32 MEASUREMENT, INT64 INT64 MEASUREMENT, FLOAT FLOAT MEASUREMENT, DOUBLE DOUBLE MEASUREMENT," |
| "TEXT TEXT MEASUREMENT, TIMESTAMP TIMESTAMP MEASUREMENT, DATE DATE MEASUREMENT, BLOB BLOB MEASUREMENT, STRING STRING MEASUREMENT)" |
| ) |
| |
| # 1、General scenario |
| expect = 10 |
| table_name = "table_b" |
| column_names = [ |
| "id1", |
| "id2", |
| "id3", |
| "attr1", |
| "attr2", |
| "attr3", |
| "BOOLEAN", |
| "INT32", |
| "INT64", |
| "FLOAT", |
| "DOUBLE", |
| "TEXT", |
| "TIMESTAMP", |
| "DATE", |
| "BLOB", |
| "STRING", |
| ] |
| data_types = [ |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.BOOLEAN, |
| TSDataType.INT32, |
| TSDataType.INT64, |
| TSDataType.FLOAT, |
| TSDataType.DOUBLE, |
| TSDataType.TEXT, |
| TSDataType.TIMESTAMP, |
| TSDataType.DATE, |
| TSDataType.BLOB, |
| TSDataType.STRING, |
| ] |
| column_types = [ |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ] |
| timestamps = [] |
| values = [] |
| for row_b in range(10): |
| timestamps.append(row_b) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| False, |
| 0, |
| 0, |
| 0.0, |
| 0.0, |
| "1234567890", |
| 0, |
| date(1970, 1, 1), |
| "1234567890".encode("utf-8"), |
| "1234567890", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| -2147483648, |
| -9223372036854775808, |
| -0.12345678, |
| -0.12345678901234567, |
| "abcdefghijklmnopqrstuvwsyz", |
| -9223372036854775808, |
| date(1000, 1, 1), |
| "abcdefghijklmnopqrstuvwsyz".encode("utf-8"), |
| "abcdefghijklmnopqrstuvwsyz", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| 2147483647, |
| 9223372036854775807, |
| 0.123456789, |
| 0.12345678901234567, |
| "!@#$%^&*()_+}{|:'`~-=[];,./<>?~", |
| 9223372036854775807, |
| date(9999, 12, 31), |
| "!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"), |
| "!@#$%^&*()_+}{|:`~-=[];,./<>?~", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| 1, |
| 1, |
| 1.0, |
| 1.0, |
| "没问题", |
| 1, |
| date(1970, 1, 1), |
| "没问题".encode("utf-8"), |
| "没问题", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| -1, |
| -1, |
| 1.1234567, |
| 1.1234567890123456, |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/", |
| 11, |
| date(1970, 1, 1), |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"), |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| 10, |
| 11, |
| 4.123456, |
| 4.123456789012345, |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题", |
| 11, |
| date(1970, 1, 1), |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode( |
| "utf-8" |
| ), |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| -10, |
| -11, |
| 12.12345, |
| 12.12345678901234, |
| "test01", |
| 11, |
| date(1970, 1, 1), |
| "Hello, World!".encode("utf-8"), |
| "string01", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| None, |
| None, |
| None, |
| None, |
| None, |
| "", |
| None, |
| date(1970, 1, 1), |
| "".encode("utf-8"), |
| "", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| -0, |
| -0, |
| -0.0, |
| -0.0, |
| " ", |
| 11, |
| date(1970, 1, 1), |
| " ".encode("utf-8"), |
| " ", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_b), |
| "id2：" + str(row_b), |
| "id3：" + str(row_b), |
| "attr1:" + str(row_b), |
| "attr2:" + str(row_b), |
| "attr3:" + str(row_b), |
| True, |
| 10, |
| 11, |
| 1.1, |
| 10011.1, |
| "test01", |
| 11, |
| date(1970, 1, 1), |
| "Hello, World!".encode("utf-8"), |
| "string01", |
| ] |
| ) |
| tablet = Tablet( |
| table_name, column_names, data_types, values, timestamps, column_types |
| ) |
| session.insert_relational_tablet(tablet) |
| # Calculate the number of rows in the actual time series |
| actual = 0 |
| with session.execute_query_statement( |
| "select * from table_b" |
| ) as session_data_set: |
| print(session_data_set.get_column_names()) |
| while session_data_set.has_next(): |
| print(session_data_set.next()) |
| actual = actual + 1 |
| # Determine whether it meets expectations |
| assert expect == actual |
| |
| # 2、Including Chinese scenes |
| expect = 10 |
| table_name = "table_a" |
| column_names = [ |
| "地区", |
| "厂号", |
| "设备号", |
| "日期", |
| "时间", |
| "负责人", |
| "测点1", |
| "测点2", |
| "测点3", |
| "测点4", |
| "测点5", |
| "测点6", |
| "测点7", |
| "测点8", |
| "测点9", |
| "测点10", |
| ] |
| data_types = [ |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.BOOLEAN, |
| TSDataType.INT32, |
| TSDataType.INT64, |
| TSDataType.FLOAT, |
| TSDataType.DOUBLE, |
| TSDataType.TEXT, |
| TSDataType.TIMESTAMP, |
| TSDataType.DATE, |
| TSDataType.BLOB, |
| TSDataType.STRING, |
| ] |
| column_types = [ |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ] |
| timestamps = [] |
| values = [] |
| for row_a in range(10): |
| timestamps.append(row_a) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| False, |
| 0, |
| 0, |
| 0.0, |
| 0.0, |
| "1234567890", |
| 0, |
| date(1970, 1, 1), |
| "1234567890".encode("utf-8"), |
| "1234567890", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| -2147483648, |
| -9223372036854775808, |
| -0.12345678, |
| -0.12345678901234567, |
| "abcdefghijklmnopqrstuvwsyz", |
| -9223372036854775808, |
| date(1000, 1, 1), |
| "abcdefghijklmnopqrstuvwsyz".encode("utf-8"), |
| "abcdefghijklmnopqrstuvwsyz", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| 2147483647, |
| 9223372036854775807, |
| 0.123456789, |
| 0.12345678901234567, |
| "!@#$%^&*()_+}{|:'`~-=[];,./<>?~", |
| 9223372036854775807, |
| date(9999, 12, 31), |
| "!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"), |
| "!@#$%^&*()_+}{|:`~-=[];,./<>?~", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| 1, |
| 1, |
| 1.0, |
| 1.0, |
| "没问题", |
| 1, |
| date(1970, 1, 1), |
| "没问题".encode("utf-8"), |
| "没问题", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| -1, |
| -1, |
| 1.1234567, |
| 1.1234567890123456, |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/", |
| 11, |
| date(1970, 1, 1), |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"), |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| 10, |
| 11, |
| 4.123456, |
| 4.123456789012345, |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题", |
| 11, |
| date(1970, 1, 1), |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode( |
| "utf-8" |
| ), |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| -10, |
| -11, |
| 12.12345, |
| 12.12345678901234, |
| "test01", |
| 11, |
| date(1970, 1, 1), |
| "Hello, World!".encode("utf-8"), |
| "string01", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| None, |
| None, |
| None, |
| None, |
| None, |
| "", |
| None, |
| date(1970, 1, 1), |
| "".encode("utf-8"), |
| "", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| -0, |
| -0, |
| -0.0, |
| -0.0, |
| " ", |
| 11, |
| date(1970, 1, 1), |
| " ".encode("utf-8"), |
| " ", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row_a), |
| "id2：" + str(row_a), |
| "id3：" + str(row_a), |
| "attr1:" + str(row_a), |
| "attr2:" + str(row_a), |
| "attr3:" + str(row_a), |
| True, |
| 10, |
| 11, |
| 1.1, |
| 10011.1, |
| "test01", |
| 11, |
| date(1970, 1, 1), |
| "Hello, World!".encode("utf-8"), |
| "string01", |
| ] |
| ) |
| tablet = Tablet( |
| table_name, column_names, data_types, values, timestamps, column_types |
| ) |
| session.insert_relational_tablet(tablet) |
| # Calculate the number of rows in the actual time series |
| actual = 0 |
| with session.execute_query_statement( |
| "select * from table_a" |
| ) as session_data_set: |
| print(session_data_set.get_column_names()) |
| 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 NumpyTablet data |
| def test_insert_relational_tablet_use_numpy_tablet(): |
| with IoTDBContainer("iotdb:dev") as db: |
| db: IoTDBContainer |
| session = Session( |
| db.get_container_host_ip(), db.get_exposed_port(6667), sql_dialect="table" |
| ) |
| session.open() |
| |
| # Preparation before testing |
| session.execute_non_query_statement( |
| "create database test_insert_relational_tablet_use_numpy_tablet" |
| ) |
| session.execute_non_query_statement( |
| "use test_insert_relational_tablet_use_numpy_tablet" |
| ) |
| session.execute_non_query_statement( |
| "create table table_b(" |
| "id1 STRING ID, id2 STRING ID, id3 STRING ID, " |
| "attr1 string attribute, attr2 string attribute, attr3 string attribute," |
| "BOOLEAN BOOLEAN MEASUREMENT, INT32 INT32 MEASUREMENT, INT64 INT64 MEASUREMENT, FLOAT FLOAT MEASUREMENT, DOUBLE DOUBLE MEASUREMENT," |
| "TEXT TEXT MEASUREMENT, TIMESTAMP TIMESTAMP MEASUREMENT, DATE DATE MEASUREMENT, BLOB BLOB MEASUREMENT, STRING STRING MEASUREMENT)" |
| ) |
| session.execute_non_query_statement( |
| "create table table_d(" |
| "id1 STRING ID, id2 STRING ID, id3 STRING ID, " |
| "attr1 string attribute, attr2 string attribute, attr3 string attribute," |
| "BOOLEAN BOOLEAN MEASUREMENT, INT32 INT32 MEASUREMENT, INT64 INT64 MEASUREMENT, FLOAT FLOAT MEASUREMENT, DOUBLE DOUBLE MEASUREMENT," |
| "TEXT TEXT MEASUREMENT, TIMESTAMP TIMESTAMP MEASUREMENT, DATE DATE MEASUREMENT, BLOB BLOB MEASUREMENT, STRING STRING MEASUREMENT)" |
| ) |
| |
| # 1、No null |
| expect = 10 |
| table_name = "table_b" |
| column_names = [ |
| "id1", |
| "id2", |
| "id3", |
| "attr1", |
| "attr2", |
| "attr3", |
| "BOOLEAN", |
| "INT32", |
| "INT64", |
| "FLOAT", |
| "DOUBLE", |
| "TEXT", |
| "TIMESTAMP", |
| "DATE", |
| "BLOB", |
| "STRING", |
| ] |
| data_types = [ |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.BOOLEAN, |
| TSDataType.INT32, |
| TSDataType.INT64, |
| TSDataType.FLOAT, |
| TSDataType.DOUBLE, |
| TSDataType.TEXT, |
| TSDataType.TIMESTAMP, |
| TSDataType.DATE, |
| TSDataType.BLOB, |
| TSDataType.STRING, |
| ] |
| column_types = [ |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ] |
| np_timestamps = np.arange(0, 10, dtype=np.dtype(">i8")) |
| np_values = [ |
| np.array(["id1:{}".format(i) for i in range(0, 10)]), |
| np.array(["id2:{}".format(i) for i in range(0, 10)]), |
| np.array(["id3:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr1:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr2:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr3:{}".format(i) for i in range(0, 10)]), |
| 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_tablet = NumpyTablet( |
| table_name, |
| column_names, |
| data_types, |
| np_values, |
| np_timestamps, |
| column_types=column_types, |
| ) |
| session.insert_relational_tablet(np_tablet) |
| # Calculate the number of rows in the actual time series |
| actual = 0 |
| with session.execute_query_statement( |
| "select * from table_b" |
| ) as session_data_set: |
| print(session_data_set.get_column_names()) |
| while session_data_set.has_next(): |
| print(session_data_set.next()) |
| actual = actual + 1 |
| # Determine whether it meets expectations |
| assert expect == actual |
| |
| # 2、Contains null |
| expect = 10 |
| table_name = "table_d" |
| column_names = [ |
| "id1", |
| "id2", |
| "id3", |
| "attr1", |
| "attr2", |
| "attr3", |
| "BOOLEAN", |
| "INT32", |
| "INT64", |
| "FLOAT", |
| "DOUBLE", |
| "TEXT", |
| "TIMESTAMP", |
| "DATE", |
| "BLOB", |
| "STRING", |
| ] |
| data_types = [ |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.BOOLEAN, |
| TSDataType.INT32, |
| TSDataType.INT64, |
| TSDataType.FLOAT, |
| TSDataType.DOUBLE, |
| TSDataType.TEXT, |
| TSDataType.TIMESTAMP, |
| TSDataType.DATE, |
| TSDataType.BLOB, |
| TSDataType.STRING, |
| ] |
| column_types = [ |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ] |
| np_timestamps = np.arange(0, 10, dtype=np.dtype(">i8")) |
| np_values = [ |
| np.array(["id1:{}".format(i) for i in range(0, 10)]), |
| np.array(["id2:{}".format(i) for i in range(0, 10)]), |
| np.array(["id3:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr1:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr2:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr3:{}".format(i) for i in range(0, 10)]), |
| 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_bitmaps_ = [] |
| for i in range(len(column_types)): |
| np_bitmaps_.append(BitMap(len(np_timestamps))) |
| 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_bitmaps_[10].mark(8) |
| np_bitmaps_[11].mark(9) |
| np_bitmaps_[12].mark(8) |
| np_bitmaps_[13].mark(9) |
| np_bitmaps_[14].mark(8) |
| np_tablet = NumpyTablet( |
| table_name, |
| column_names, |
| data_types, |
| np_values, |
| np_timestamps, |
| bitmaps=np_bitmaps_, |
| column_types=column_types, |
| ) |
| session.insert_relational_tablet(np_tablet) |
| # Calculate the number of rows in the actual time series |
| actual = 0 |
| with session.execute_query_statement( |
| "select * from table_d" |
| ) as session_data_set: |
| print(session_data_set.get_column_names()) |
| 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 creation |
| def test_insert_relational_tablet_auto_create(): |
| with IoTDBContainer("iotdb:dev") as db: |
| db: IoTDBContainer |
| session = Session( |
| db.get_container_host_ip(), db.get_exposed_port(6667), sql_dialect="table" |
| ) |
| session.open() |
| |
| # Preparation before testing |
| session.execute_non_query_statement( |
| "create database test_insert_relational_tablet_use_numpy_tablet" |
| ) |
| session.execute_non_query_statement( |
| "use test_insert_relational_tablet_use_numpy_tablet" |
| ) |
| |
| # 1、Test inserting tablet data(Insert 10 times) |
| for i in range(1, 10): |
| table_name = "t" + str(i) |
| column_names = [ |
| "id1", |
| "id2", |
| "id3", |
| "attr1", |
| "attr2", |
| "attr3", |
| "BOOLEAN", |
| "INT32", |
| "INT64", |
| "FLOAT", |
| "DOUBLE", |
| "TEXT", |
| "TIMESTAMP", |
| "DATE", |
| "BLOB", |
| "STRING", |
| ] |
| data_types = [ |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.BOOLEAN, |
| TSDataType.INT32, |
| TSDataType.INT64, |
| TSDataType.FLOAT, |
| TSDataType.DOUBLE, |
| TSDataType.TEXT, |
| TSDataType.TIMESTAMP, |
| TSDataType.DATE, |
| TSDataType.BLOB, |
| TSDataType.STRING, |
| ] |
| column_types = [ |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ] |
| timestamps = [] |
| values = [] |
| for row in range(10): |
| timestamps.append(row) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| False, |
| 0, |
| 0, |
| 0.0, |
| 0.0, |
| "1234567890", |
| 0, |
| date(1970, 1, 1), |
| "1234567890".encode("utf-8"), |
| "1234567890", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| -2147483648, |
| -9223372036854775808, |
| -0.12345678, |
| -0.12345678901234567, |
| "abcdefghijklmnopqrstuvwsyz", |
| -9223372036854775808, |
| date(1000, 1, 1), |
| "abcdefghijklmnopqrstuvwsyz".encode("utf-8"), |
| "abcdefghijklmnopqrstuvwsyz", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| 2147483647, |
| 9223372036854775807, |
| 0.123456789, |
| 0.12345678901234567, |
| "!@#$%^&*()_+}{|:'`~-=[];,./<>?~", |
| 9223372036854775807, |
| date(9999, 12, 31), |
| "!@#$%^&*()_+}{|:`~-=[];,./<>?~".encode("utf-8"), |
| "!@#$%^&*()_+}{|:`~-=[];,./<>?~", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| 1, |
| 1, |
| 1.0, |
| 1.0, |
| "没问题", |
| 1, |
| date(1970, 1, 1), |
| "没问题".encode("utf-8"), |
| "没问题", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| -1, |
| -1, |
| 1.1234567, |
| 1.1234567890123456, |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/", |
| 11, |
| date(1970, 1, 1), |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/".encode("utf-8"), |
| "！@#￥%……&*（）——|：“《》？·【】、；‘，。/", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| 10, |
| 11, |
| 4.123456, |
| 4.123456789012345, |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:'`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题", |
| 11, |
| date(1970, 1, 1), |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题".encode( |
| "utf-8" |
| ), |
| "1234567890abcdefghijklmnopqrstuvwsyz!@#$%^&*()_+}{|:`~-=[];,./<>?~！@#￥%……&*（）——|：“《》？·【】、；‘，。/没问题", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| -10, |
| -11, |
| 12.12345, |
| 12.12345678901234, |
| "test01", |
| 11, |
| date(1970, 1, 1), |
| "Hello, World!".encode("utf-8"), |
| "string01", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| None, |
| None, |
| None, |
| None, |
| None, |
| "", |
| None, |
| date(1970, 1, 1), |
| "".encode("utf-8"), |
| "", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| -0, |
| -0, |
| -0.0, |
| -0.0, |
| " ", |
| 11, |
| date(1970, 1, 1), |
| " ".encode("utf-8"), |
| " ", |
| ] |
| ) |
| values.append( |
| [ |
| "id1：" + str(row), |
| "id2：" + str(row), |
| "id3：" + str(row), |
| "attr1:" + str(row), |
| "attr2:" + str(row), |
| "attr3:" + str(row), |
| True, |
| 10, |
| 11, |
| 1.1, |
| 10011.1, |
| "test01", |
| 11, |
| date(1970, 1, 1), |
| "Hello, World!".encode("utf-8"), |
| "string01", |
| ] |
| ) |
| tablet = Tablet( |
| table_name, column_names, data_types, values, timestamps, column_types |
| ) |
| session.insert_relational_tablet(tablet) |
| |
| # 2、Test inserting NumpyTablet data(Insert 10 times) |
| for i in range(1, 10): |
| table_name = "t" + str(i) |
| column_names = [ |
| "id1", |
| "id2", |
| "id3", |
| "attr1", |
| "attr2", |
| "attr3", |
| "BOOLEAN", |
| "INT32", |
| "INT64", |
| "FLOAT", |
| "DOUBLE", |
| "TEXT", |
| "TIMESTAMP", |
| "DATE", |
| "BLOB", |
| "STRING", |
| ] |
| data_types = [ |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.STRING, |
| TSDataType.BOOLEAN, |
| TSDataType.INT32, |
| TSDataType.INT64, |
| TSDataType.FLOAT, |
| TSDataType.DOUBLE, |
| TSDataType.TEXT, |
| TSDataType.TIMESTAMP, |
| TSDataType.DATE, |
| TSDataType.BLOB, |
| TSDataType.STRING, |
| ] |
| column_types = [ |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ID, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.ATTRIBUTE, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ColumnType.MEASUREMENT, |
| ] |
| np_timestamps = np.arange(0, 10, dtype=np.dtype(">i8")) |
| np_values = [ |
| np.array(["id1:{}".format(i) for i in range(0, 10)]), |
| np.array(["id2:{}".format(i) for i in range(0, 10)]), |
| np.array(["id3:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr1:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr2:{}".format(i) for i in range(0, 10)]), |
| np.array(["attr3:{}".format(i) for i in range(0, 10)]), |
| 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_tablet = NumpyTablet( |
| table_name, |
| column_names, |
| data_types, |
| np_values, |
| np_timestamps, |
| column_types=column_types, |
| ) |
| session.insert_relational_tablet(np_tablet) |
| |
| session.close() |
