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# Hive-TsFile

## About Hive-TsFile-Connector

Hive-TsFile-Connector implements the support of Hive for external data sources of Tsfile type. This enables users to operate TsFile by Hive.

With this connector, you can

* Load a single TsFile, from either the local file system or hdfs, into hive
* Load all files in a specific directory, from either the local file system or hdfs, into hive
* Query the tsfile through HQL.
* As of now, the write operation is not supported in hive-connector. So, insert operation in HQL is not allowed while operating tsfile through hive.

## System Requirements

|Hadoop Version |Hive Version | Java Version | TsFile |
|-------------  |------------ | ------------ |------------ |
| `2.7.3` or `3.2.1`       |    `2.3.6` or `3.1.2`  | `1.8`        | `1.0.0`|

> Note: For more information about how to download and use TsFile, please see the following link: https://github.com/apache/iotdb/tree/master/tsfile.

## Data Type Correspondence

| TsFile data type | Hive field type |
| ---------------- | --------------- |
| BOOLEAN          | Boolean         |
| INT32            | INT             |
| INT64       	   | BIGINT          |
| FLOAT       	   | Float           |
| DOUBLE      	   | Double          |
| TEXT      	   | STRING          |


## Add Dependency For Hive

To use hive-connector in hive, we should add the hive-connector jar into hive.

After downloading the code of iotdb from <https://github.com/apache/iotdb>, you can use the command of `mvn clean package -pl iotdb-connector/hive-connector -am -Dmaven.test.skip=true -P get-jar-with-dependencies` to get a `hive-connector-X.X.X-jar-with-dependencies.jar`.

Then in hive, use the command of `add jar XXX` to add the dependency. For example:

```
hive> add jar /Users/hive/iotdb/hive-connector/target/hive-connector-1.0.0-jar-with-dependencies.jar;

Added [/Users/hive/iotdb/hive-connector/target/hive-connector-1.0.0-jar-with-dependencies.jar] to class path
Added resources: [/Users/hive/iotdb/hive-connector/target/hive-connector-1.0.0-jar-with-dependencies.jar]
```


## Create Tsfile-backed Hive tables

To create a Tsfile-backed table, specify the `serde` as `org.apache.iotdb.hive.TsFileSerDe`, 
specify the `inputformat` as `org.apache.iotdb.hive.TSFHiveInputFormat`, 
and the `outputformat` as `org.apache.iotdb.hive.TSFHiveOutputFormat`.

Also provide a schema which only contains two fields: `time_stamp` and `sensor_id` for the table. 
`time_stamp` is the time value of the time series 
and `sensor_id` is the sensor name to extract from the tsfile to hive such as `sensor_1`. 
The name of the table can be any valid table names in hive.

Also a location provided for hive-connector to pull the most current data for the table.

The location should be a specific directory on your local file system or HDFS to set up Hadoop.
If it is in your local file system, the location should look like `file:///data/data/sequence/root.baic2.WWS.leftfrontdoor/`

Last, set the `device_id` in `TBLPROPERTIES` to the device name you want to analyze.

For example:

```
CREATE EXTERNAL TABLE IF NOT EXISTS only_sensor_1(
  time_stamp TIMESTAMP,
  sensor_1 BIGINT)
ROW FORMAT SERDE 'org.apache.iotdb.hive.TsFileSerDe'
STORED AS
  INPUTFORMAT 'org.apache.iotdb.hive.TSFHiveInputFormat'
  OUTPUTFORMAT 'org.apache.iotdb.hive.TSFHiveOutputFormat'
LOCATION '/data/data/sequence/root.baic2.WWS.leftfrontdoor/'
TBLPROPERTIES ('device_id'='root.baic2.WWS.leftfrontdoor.plc1');
```
In this example, the data of `root.baic2.WWS.leftfrontdoor.plc1.sensor_1` is pulled from the directory of `/data/data/sequence/root.baic2.WWS.leftfrontdoor/`. 
This table results in a description as below:

```
hive> describe only_sensor_1;
OK
time_stamp          	timestamp              	from deserializer
sensor_1            	bigint              	from deserializer
Time taken: 0.053 seconds, Fetched: 2 row(s)
```
At this point, the Tsfile-backed table can be worked with in Hive like any other table.

## Query from TsFile-backed Hive tables

Before we do any queries, we should set the `hive.input.format` in hive by executing the following command.

```
hive> set hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat;
```

Now, we already have an external table named `only_sensor_1` in hive. 
We can use any query operations through HQL to analyse it.

For example:

### Select Clause Example

```
hive> select * from only_sensor_1 limit 10;
OK
1	1000000
2	1000001
3	1000002
4	1000003
5	1000004
6	1000005
7	1000006
8	1000007
9	1000008
10	1000009
Time taken: 1.464 seconds, Fetched: 10 row(s)
```

### Aggregate Clause Example

```
hive> select count(*) from only_sensor_1;
WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
Query ID = jackietien_20191016202416_d1e3e233-d367-4453-b39a-2aac9327a3b6
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks determined at compile time: 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Job running in-process (local Hadoop)
2019-10-16 20:24:18,305 Stage-1 map = 0%,  reduce = 0%
2019-10-16 20:24:27,443 Stage-1 map = 100%,  reduce = 100%
Ended Job = job_local867757288_0002
MapReduce Jobs Launched:
Stage-Stage-1:  HDFS Read: 0 HDFS Write: 0 SUCCESS
Total MapReduce CPU Time Spent: 0 msec
OK
1000000
Time taken: 11.334 seconds, Fetched: 1 row(s)
```