No.9 - 时序数据库随笔 - Apache IoTDB 多条时序数据联合分析

No.9 - 时序数据库随笔 - Apache IoTDB 多条时序数据联合分析

01 问题

本篇我们一起来看看Apache IoTDB如何解决要解决​​No8​​​提到的网友问题，如下：

​简单说就是如何处理两条时间线的数值计算？上面例子是一个 “+” 加法。

02 数据准备

要处理多条时序数据分析问题，我们首先先建立两条时间序列，我们做一下数据准备：

启动IoTDB服务实例

我们首先源码编译Master最新代码(),并启动服务实例。如下

iotdb git:(master) mvn clean install -DskipTests ... ...[INFO] -------------------------------------------[INFO] BUILD SUCCESS[INFO] -------------------------------------------[INFO] Total time: 02:41 min[INFO] Finished at: 2021-04-07T07:13:32+08:00[INFO] -------------------------------------------➜ iotdb git:(master) cd distribution/target/apache-iotdb-0.12.0-SNAPSHOT-server-bin/apache-iotdb-0.12.0-SNAPSHOT-server-bin/➜ apache-iotdb-0.12.0-SNAPSHOT-server-bin git:(master) sbin/start-server.sh ---------------------Starting IoTDB......2021-04-07 07:33:50,636 [main] INFO o.a.i.db.service.IoTDB:93 - IoTDB has started.

启动Cli

➜ iotdb git:(master) cd distribution/target/apache-iotdb-0.12.0-SNAPSHOT-server-bin/apache-iotdb-0.12.0-SNAPSHOT-server-bin/➜ apache-iotdb-0.12.0-SNAPSHOT-server-bin git:(master) sbin/start-cli.sh -h 127.0.0.1 -p 6667 -u root -pw root

创建存储组

IoTDB> set storage group to root.lemming

创建时间线

IoTDB> create timeseries root.lemming.device1.m1 with datatype=FLOAT,encoding=RLEIoTDB> create timeseries root.lemming.device1.m2 with datatype=FLOAT,encoding=RLE...IoTDB> show timeseries;

插入时间序列数据

IoTDB> insert into root.lemming.device1(timestamp,m1, m2) values(1,3333,4444)IoTDB> select * from root.lemming.device1;

看到这里，不知道大家是否发现，IoTDB虽然在存储层面是按时间序列进行列存储的，但是在API层面已经为大家抽象好来二维表结构，大家可以把多个时间序列当成一张二维度表的不同列,这个抽象大家就免去来入在InfluxDB中利用PIVOT进行行转列的需求，这样就更方便理解和对多时序数据的进行查询分析。好，那么下面我们看看如果实现 m1 + m2 这个需求。

03 代码数据准备

我们一个一个敲命令不如咱直接写个Java代码实例，方便反复测试，测试本篇内容，我们只需要依赖iotdb-jdbc模块，pom如下：

org.apache.iotdb iotdb-jdbc ${iotdb.version}

创建存储组，时间序列和准备数据的测试代码如下：

public class No9JDBCExample { /** * 第一次运行 init(),如果一切顺利，正面环境和数据准备完成 */ public static void main(String[] args) throws Exception { Class.forName("org.apache.iotdb.jdbc.IoTDBDriver"); try (Connection connection = DriverManager.getConnection("jdbc:iotdb://127.0.0.1:6667/", "root", "root"); Statement statement = connection.createStatement()) { init(statement); } catch (IoTDBSQLException e) { e.printStackTrace(); } } public static void init(Statement statement) throws Exception { setStorageGroup(statement); statement.execute( "CREATE TIMESERIES root.lemming.device1.m1 with datatype=FLOAT,encoding=RLE"); statement.execute( "CREATE TIMESERIES root.lemming.device1.m2 with datatype=FLOAT,encoding=RLE"); statement.execute("INSERT INTO root.lemming.device1(timestamp,m1, m2) VALUES (1,3333,4444)"); ResultSet resultSet = statement.executeQuery("SELECT timestamp, m1 as m1, m2 as m2 FROM root.lemming.device1"); outputResult(resultSet); } public static void setStorageGroup(Statement statement) throws Exception{ try { statement.execute("SET STORAGE GROUP TO root.lemming"); }catch (Exception e){ statement.execute("DELETE STORAGE GROUP root.lemming"); statement.execute("SET STORAGE GROUP TO root.lemming"); } } private static void outputResult(ResultSet resultSet) throws SQLException { if (resultSet != null) { System.out.println("--------------------------"); final ResultSetMetaData metaData = resultSet.getMetaData(); final int columnCount = metaData.getColumnCount(); for (int i = 0; i < columnCount; i++) { System.out.print(metaData.getColumnLabel(i + 1) + " "); } System.out.println(); while (resultSet.next()) { for (int i = 1; ; i++) { System.out.print(resultSet.getString(i)); if (i < columnCount) { System.out.print(", "); } else { System.out.println(); break; } } } System.out.println("--------------------------\n"); } }}

如果你运行得到如下结果，正面一切准备工作就绪：

04 UDF解决加法

我们接下来看看Apache IoTDB如何解决加法问题，目前IoTDB提供来自定义UDF的方式解决用户自定义的操作。如果要使用UDF我们需要增加依赖如下：

org.apache.iotdb iotdb-server 0.12.0-SNAPSHOT provided

添加依赖之后，我们可以实现如下UDTF(User Defined Timeseries Generating Function), 这里写一下全称，不然大家会以为是User defined Table Function。当然不可否则，UDF的接口我们还可以有改进的空间，我们就目前现状与大家简单说明，如下：

public interface UDTF extends UDF { /** * This method is mainly used to customize UDTF. In this method, the user can do the following * things: * *

*
• Use UDFParameters to get the time series paths and parse key-value pair attributes * entered by the user. *
• Set the strategy to access the original data and set the output data type in * UDTFConfigurations. *
• Create resources, such as establishing external connections, opening files, etc. *

This method is called after the UDTF is instantiated and before the beginning of the * transformation process. * * @param parameters used to parse the input parameters entered by the user * @param configurations used to set the required properties in the UDTF * @throws Exception the user can throw errors if necessary */ @SuppressWarnings("squid:S112") void beforeStart(UDFParameters parameters, UDTFConfigurations configurations) throws Exception; /** * When the user specifies {@link RowByRowAccessStrategy} to access the original data in {@link * UDTFConfigurations}, this method will be called to process the transformation. In a single UDF * query, this method may be called multiple times. * * @param row original input data row (aligned by time) * @param collector used to collect output data points * @throws Exception the user can throw errors if necessary * @see RowByRowAccessStrategy */ @SuppressWarnings("squid:S112") default void transform(Row row, PointCollector collector) throws Exception {} /** * When the user specifies {@link SlidingSizeWindowAccessStrategy} or {@link * SlidingTimeWindowAccessStrategy} to access the original data in {@link UDTFConfigurations}, * this method will be called to process the transformation. In a single UDF query, this method * may be called multiple times. * * @param rowWindow original input data window (rows inside the window are aligned by time) * @param collector used to collect output data points * @throws Exception the user can throw errors if necessary * @see SlidingSizeWindowAccessStrategy * @see SlidingTimeWindowAccessStrategy */ @SuppressWarnings("squid:S112") default void transform(RowWindow rowWindow, PointCollector collector) throws Exception {} /** * This method will be called once after all {@link UDTF#transform(Row, PointCollector) calls or * {@link UDTF#transform(RowWindow, PointCollector) calls have been executed. In a single UDF * query, this method will and will only be called once. * * @param collector used to collect output data points * @throws Exception the user can throw errors if necessary */ @SuppressWarnings("squid:S112") default void terminate(PointCollector collector) throws Exception {}}

其中最核心的是transform方法，对transform的实现逻辑就是我们业务的需求逻辑，面对我们要实现 加法 的逻辑，我们的核心逻辑就是transform实现，如下：

public class AddFunc implements UDTF {...... @Override public void transform(Row row, PointCollector collector) throws Exception { if (row.isNull(0) || row.isNull(1)) { return; } collector.putLong( row.getTime(), (long) (extractDoubleValue(row, 0) + extractDoubleValue(row, 1) + addend)); } private double extractDoubleValue(Row row, int index) { double value; switch (row.getDataType(index)) { case INT32: value = row.getInt(index); break; case INT64: value = (double) row.getLong(index); break; case FLOAT: value = row.getFloat(index); break; case DOUBLE: value = row.getDouble(index); break; default: throw new UnSupportedDataTypeException(row.getDataType(index).toString()); } return value; }}

当然开发完UDF，你还需要编写查询逻辑，如下：

public static void udf(Statement statement) { try{ statement.execute("CREATE FUNCTION plus AS \"org.khkw.iotdb.no9.AddFunc\""); statement.execute("SHOW FUNCTIONS"); ResultSet resultSet = statement.executeQuery("SELECT timestamp, plus(m1, m2) FROM root.lemming.device1"); outputResult(resultSet); }catch (Exception e) { e.printStackTrace(); } }

如上代码我们注册了名为 plus的UDF，然后plus(m1, m2)的方式实现了加法需求。当然，我们还不能直接运行udf方法，直接运行会报出找不到rg.khkw.iotdb.no9.AddFunc类，如下：

这是因为IoTDB配置udf的JAR加载需要指定JAR所在目录，我们利用 mvn clean package 生成JAR，然后再修改一下iotdb-engine.properties配置文件，如下：

我配置成为自己项目的jar所在路径了，如下：

配置完成之后，重新启动IoTDB服务实例。启动日志你会发现对UDF的加载：

➜ apache-iotdb-0.12.0-SNAPSHOT-server-bin git:(master) sbin/start-server.sh 。。。。。。2021-04-07 08:17:53,398 [main] INFO o.a.i.d.q.u.s.UDFClassLoaderManager:56 - UDF lib root: /Users/jincheng/work/know_how_know_why/khkw_iotdb/No9udf/target 。。。2021-04-07 12:34:11,622 [main] INFO o.a.i.d.s.t.ThriftService:125 - IoTDB: start RPC ServerService successfully, listening on ip 0.0.0.0 port 6667

确保我们自定义的UDF已经被加载之后，我们运行udf，如下：

好，到目前我们利用UDF解决了加法需求，那么UDF是否可以在CLI里面使用呢？

05 CLI使用UDF

当然，我们可以在CLI里面使用UDF，我们启动一个CLI客户端,并用命令 SHOW FUNCTIONS 显示已有的FUNCTIONS，如下：

发现我们自定义的UDF已经在刚才运行Java程序时候注册了，我们可以删除让后在CLI在操作一遍（演示作用），如下：

IoTDB> CREATE FUNCTION plus AS "org.khkw.iotdb.no9.AddFunc"Msg: 411: Failed to register non-TEMPORARY UDF PLUS(org.khkw.iotdb.no9.AddFunc), because a non-TEMPORARY UDF PLUS(org.khkw.iotdb.no9.AddFunc) with the same function name and the class name has already been registered.IoTDB> DROP FUNCTION plusMsg: The statement is executed successfully.IoTDB> CREATE FUNCTION plus AS "org.khkw.iotdb.no9.AddFunc"Msg: The statement is executed successfully.IoTDB> SELECT timestamp, plus(m1, m2) FROM root.lemming.device1;+-----------------------------+------------------------------------------------------+| Time|plus(root.lemming.device1.m1, root.lemming.device1.m2)|+-----------------------------+------------------------------------------------------+|1970-01-01T08:00:00.001+08:00| 7777|+-----------------------------+------------------------------------------------------+Total line number = 1It costs 0.552s

OK,到这里不论是Java方式还是CLI方式我们都完成了 多时序数据联合分析的需求。

06 贡献社区

上面我们发现IoTDB利用UDF的方式解决加法问题，虽然是通用做法，但是我们还可以做的更好，比如直接支持 m1 + m2 这种（加/减/乘/除）的便捷运算，所以这是你贡献的好机会，社区JIRA等你take。

作者介绍

孙金城，51CTO社区编辑，Apache Flink PMC 成员，Apache Beam Committer，Apache IoTDB PMC 成员，ALC Beijing 成员，Apache ShenYu 导师，Apache 软件基金会成员。关注技术领域流计算和时序数据存储。

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