新一代数据湖存储技术Apache Paimon入门Demo

目录

前言

1. 什么是 Apache Paimon

一、本地环境快速上手

1、本地Flink伪集群

2、IDEA中跑Paimon Demo

2.1 代码

2.2 IDEA中成功运行

3、IDEA中Stream读写

3.1 流写

3.2 流读(toChangeLogStream)

二、进阶:本地(IDEA)多流拼接测试

要解决的问题:

note:

1、'changelog-producer' = 'full-compaction'

(1)multiWrite代码

(2)读延迟

2、'changelog-producer' = 'lookup'

三、可能遇到的问题


前言

1. 什么是 Apache Paimon

        Apache Paimon (incubating) 是一项流式数据湖存储技术,可以为用户提供高吞吐、低延迟的数据摄入、流式订阅以及实时查询能力。

        Paimon 采用开放的数据格式和技术理念,可以与 Apache Flink / Spark / Trino 等诸多业界主流计算引擎进行对接,共同推进 Streaming Lakehouse 架构的普及和发展。

新一代数据湖存储技术Apache Paimon入门Demo_第1张图片

        Paimon 以湖存储的方式基于分布式文件系统管理元数据,并采用开放的 ORC、Parquet、Avro 文件格式,支持各大主流计算引擎,包括 Flink、Spark、Hive、Trino、Presto。未来会对接更多引擎,包括 Doris 和 Starrocks。

官网:https://paimon.apache.org/ 

Github:https://github.com/apache/incubator-paimon

以下为快速入门上手Paimon的example:

一、本地环境快速上手

基于paimon 0.4-SNAPSHOT (Flink 1.14.4),Flink版本太低是不支持的,paimon基于最低版本1.14.6,经尝试在Flink1.14.0是不可以的!

paimon-flink-1.14-0.4-20230504.002229-50.jar

1、本地Flink伪集群

0. 需要先下载jar包,并添加至flink的lib中;

1. 根据官网demo,启动flinksql-client,创建catalog,创建表,创建数据源(视图),insert数据到表中。

新一代数据湖存储技术Apache Paimon入门Demo_第2张图片

2. 通过 localhost:8081 查看 Flink UI

新一代数据湖存储技术Apache Paimon入门Demo_第3张图片

3. 查看filesystem数据、元数据文件

新一代数据湖存储技术Apache Paimon入门Demo_第4张图片

2、IDEA中跑Paimon Demo

pom依赖:

        
            org.apache.paimon
            paimon-flink-1.14
            0.4-SNAPSHOT
        

拉取不到的可以手动添加到本地maven仓库:

mvn install:install-file -DgroupId=org.apache.paimon -DartifactId=paimon-flink-1.14 -Dversion=0.4-SNAPSHOT -Dpackaging=jar -Dfile=D:\software\paimon-flink-1.14-0.4-20230504.002229-50.jar

2.1 代码

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

/**
 * @Author: YK.Leo
 * @Date: 2023-05-14 15:12
 * @Version: 1.0
 */

// Succeed at local !!!
public class OfficeDemoV1 {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);
        env.enableCheckpointing(10000l);
        env.getCheckpointConfig().setCheckpointStorage("file:/D:/tmp/paimon/");

        TableEnvironment tableEnv = StreamTableEnvironment.create(env);

        // 0. Create a Catalog and a Table
        tableEnv.executeSql("CREATE CATALOG my_catalog_api WITH (\n" +
                "    'type'='paimon',\n" +                           // todo: !!!
                "    'warehouse'='file:///D:/tmp/paimon'\n" +
                ")");

        tableEnv.executeSql("USE CATALOG my_catalog_api");

        tableEnv.executeSql("CREATE TABLE IF NOT EXISTS word_count_api (\n" +
                "    word STRING PRIMARY KEY NOT ENFORCED,\n" +
                "    cnt BIGINT\n" +
                ")");

        // 1. Write Data
        tableEnv.executeSql("CREATE TEMPORARY TABLE IF NOT EXISTS word_table_api (\n" +
                "    word STRING\n" +
                ") WITH (\n" +
                "    'connector' = 'datagen',\n" +
                "    'fields.word.length' = '1'\n" +
                ")");

        // tableEnv.executeSql("SET 'execution.checkpointing.interval' = '10 s'");

        tableEnv.executeSql("INSERT INTO word_count_api SELECT word, COUNT(*) FROM word_table_api GROUP BY word");

        env.execute();
    }
}

2.2 IDEA中成功运行

新一代数据湖存储技术Apache Paimon入门Demo_第5张图片

3、IDEA中Stream读写

3.1 流写

代码:

package com.study.flink.table.paimon.demo;

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.StatementSet;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

/**
 * @Author: YK.Leo
 * @Date: 2023-05-17 11:11
 * @Version: 1.0
 */

// succeed at local !!!
public class OfficeStreamsWriteV2 {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);
        env.enableCheckpointing(10000L);
        env.getCheckpointConfig().setCheckpointStorage("file:/D:/tmp/paimon/");

        TableEnvironment tableEnv = StreamTableEnvironment.create(env);


        // 0. Create a Catalog and a Table
        tableEnv.executeSql("CREATE CATALOG my_catalog_local WITH (\n" +
                "    'type'='paimon',\n" +                           // todo: !!!
                "    'warehouse'='file:///D:/tmp/paimon'\n" +
                ")");

        tableEnv.executeSql("USE CATALOG my_catalog_local");

        tableEnv.executeSql("CREATE DATABASE IF NOT EXISTS my_catalog_local.local_db");
        tableEnv.executeSql("USE local_db");

        // drop tbl
        tableEnv.executeSql("DROP TABLE IF EXISTS paimon_tbl_streams");
        tableEnv.executeSql("CREATE TABLE IF NOT EXISTS paimon_tbl_streams(\n"
                + " uuid bigint,\n"
                + " name VARCHAR(3),\n"
                + " age int,\n"
                + " ts TIMESTAMP(3),\n"
                + " dt VARCHAR(10), \n"
                + " PRIMARY KEY (dt, uuid) NOT ENFORCED \n"
                + ") PARTITIONED BY (dt) \n"
                + " WITH (\n" +
                "    'merge-engine' = 'partial-update',\n" +
                "    'changelog-producer' = 'full-compaction', \n" +
                "    'file.format' = 'orc', \n" +
                "    'scan.mode' = 'compacted-full', \n" +
                "    'bucket' = '5', \n" +
                "    'sink.parallelism' = '5', \n" +
                "    'sequence.field' = 'ts' \n" +   // todo, to check
                ")"
        );

        // datagen ====================================================================
        tableEnv.executeSql("CREATE TEMPORARY TABLE IF NOT EXISTS source_A (\n" +
                " uuid bigint PRIMARY KEY NOT ENFORCED,\n" +
                " `name` VARCHAR(3)," +
                " _ts1 TIMESTAMP(3)\n" +
                ") WITH (\n" +
                " 'connector' = 'datagen', \n" +
                " 'fields.uuid.kind'='sequence',\n" +
                " 'fields.uuid.start'='0', \n" +
                " 'fields.uuid.end'='1000000', \n" +
                " 'rows-per-second' = '1' \n" +
                ")");
        tableEnv.executeSql("CREATE TEMPORARY TABLE IF NOT EXISTS source_B (\n" +
                " uuid bigint PRIMARY KEY NOT ENFORCED,\n" +
                " `age` int," +
                " _ts2 TIMESTAMP(3)\n" +
                ") WITH (\n" +
                " 'connector' = 'datagen', \n" +
                " 'fields.uuid.kind'='sequence',\n" +
                " 'fields.uuid.start'='0', \n" +
                " 'fields.uuid.end'='1000000', \n" +
                " 'rows-per-second' = '1' \n" +
                ")");

        //
        //tableEnv.executeSql("insert into paimon_tbl_streams(uuid, name, _ts1) select uuid, concat(name,'_A') as name, _ts1 from source_A");
        //tableEnv.executeSql("insert into paimon_tbl_streams(uuid, age, _ts1) select uuid, concat(age,'_B') as age, _ts1 from source_B");
        StatementSet statementSet = tableEnv.createStatementSet();
        statementSet
                .addInsertSql("insert into paimon_tbl_streams(uuid, name, ts, dt) select uuid, name, _ts1 as ts, date_format(_ts1,'yyyy-MM-dd') as dt from source_A")
                .addInsertSql("insert into paimon_tbl_streams(uuid, age, dt) select uuid, age, date_format(_ts2,'yyyy-MM-dd') as dt from source_B")
                ;

        statementSet.execute();
        // env.execute();
    }
}

结果:

新一代数据湖存储技术Apache Paimon入门Demo_第6张图片

3.2 流读(toChangeLogStream)

代码:

package com.study.flink.table.paimon.demo;

import org.apache.flink.api.common.functions.FilterFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Schema;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.table.connector.ChangelogMode;
import org.apache.flink.types.Row;
import org.apache.flink.types.RowKind;
import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;

/**
 * @Author: YK.Leo
 * @Date: 2023-05-15 18:50
 * @Version: 1.0
 */

// 流读单表OK!
public class OfficeStreamReadV1  {

    public static final Logger LOGGER = LogManager.getLogger(OfficeStreamReadV1.class);

    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        env.setParallelism(1);
        env.enableCheckpointing(10000L);
        env.getCheckpointConfig().setCheckpointStorage("file:/D:/tmp/paimon/");

        TableEnvironment tableEnv = StreamTableEnvironment.create(env);


        // 0. Create a Catalog and a Table
        tableEnv.executeSql("CREATE CATALOG my_catalog_local WITH (\n" +
                "    'type'='paimon',\n" +                           // todo: !!!
                "    'warehouse'='file:///D:/tmp/paimon'\n" +
                ")");

        tableEnv.executeSql("USE CATALOG my_catalog_local");

        tableEnv.executeSql("CREATE DATABASE IF NOT EXISTS my_catalog_local.local_db");
        tableEnv.executeSql("USE local_db");

        // 不需要再次创建表

        // convert to DataStream
        // Table table = tableEnv.sqlQuery("SELECT * FROM paimon_tbl_streams");
        Table table = tableEnv.sqlQuery("SELECT * FROM paimon_tbl_streams WHERE name is not null and age is not null");
        // DataStream dataStream = ((StreamTableEnvironment) tableEnv).toChangelogStream(table);
        // todo : doesn't support consuming update and delete changes which is produced by node TableSourceScan
        // DataStream dataStream = ((StreamTableEnvironment) tableEnv).toDataStream(table);
        // 剔除 -U 数据(即:更新前的数据不需要重新发送,剔除)!!!
        DataStream dataStream = ((StreamTableEnvironment) tableEnv)
                .toChangelogStream(table, Schema.newBuilder().primaryKey("dt","uuid").build(), ChangelogMode.upsert())
                .filter(new FilterFunction() {
                    @Override
                    public boolean filter(Row row) throws Exception {
                        boolean isNoteUpdateBefore = !(row.getKind().equals(RowKind.UPDATE_BEFORE));
                        if (!isNoteUpdateBefore) {
                            LOGGER.info("UPDATE_BEFORE: " + row.toString());
                        }
                        return isNoteUpdateBefore;
                    }
                })
                ;

        // use this datastream
        dataStream.executeAndCollect().forEachRemaining(System.out::println);

        env.execute();
    }
}

结果:

新一代数据湖存储技术Apache Paimon入门Demo_第7张图片

二、进阶:本地(IDEA)多流拼接测试

要解决的问题:

        多个流拥有相同的主键,每个流更新除主键外的部分字段,通过主键完成多流拼接。

note:

        如果是两个Flink Job 或者 两个 pipeline 写同一个paimon表,则直接会产生conflict,其中一条流不断exception、重启;

        可以使用 “UNION ALL” 将多个流合并为一个流,最终一个Flink job写paimon表;

        使用主键表,'merge-engine' = 'partial-update'

1、'changelog-producer' = 'full-compaction'

(1)multiWrite代码

package com.study.flink.table.paimon.multi;

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.StatementSet;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

/**
 * @Author: YK.Leo
 * @Date: 2023-05-18 10:17
 * @Version: 1.0
 */

// Succeed as local !!!
// 而且不会产生conflict,跑5分钟没有任何异常(公司跑几天无异常)! 数据也可以在另一个job流读!
public class MultiStreamsUnionWriteV1 {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        env.enableCheckpointing(10*1000L);
        env.getCheckpointConfig().setCheckpointStorage("file:/D:/tmp/paimon/");
        TableEnvironment tableEnv = StreamTableEnvironment.create(env);

        // 0. Create a Catalog and a Table
        tableEnv.executeSql("CREATE CATALOG my_catalog_local WITH (\n" +
                "    'type'='paimon',\n" +                           // todo: !!!
                "    'warehouse'='file:///D:/tmp/paimon'\n" +
                ")");
        tableEnv.executeSql("USE CATALOG my_catalog_local");

        tableEnv.executeSql("CREATE DATABASE IF NOT EXISTS my_catalog_local.local_db");
        tableEnv.executeSql("USE local_db");

        // drop & create tbl
        tableEnv.executeSql("DROP TABLE IF EXISTS paimon_tbl_streams");
        tableEnv.executeSql("CREATE TABLE IF NOT EXISTS paimon_tbl_streams(\n"
                + " uuid bigint,\n"
                + " name VARCHAR(3),\n"
                + " age int,\n"
                + " ts TIMESTAMP(3),\n"
                + " dt VARCHAR(10), \n"
                + " PRIMARY KEY (dt, uuid) NOT ENFORCED \n"
                + ") PARTITIONED BY (dt) \n"
                + " WITH (\n" +
                "    'merge-engine' = 'partial-update',\n" +
                "    'changelog-producer' = 'full-compaction', \n" +
                "    'file.format' = 'orc', \n" +
                "    'scan.mode' = 'compacted-full', \n" +
                "    'bucket' = '5', \n" +
                "    'sink.parallelism' = '5', \n" +
                // "    'write_only' = 'true', \n" +
                "    'sequence.field' = 'ts' \n" +   // todo, to check
                ")"
        );

        // datagen ====================================================================
        tableEnv.executeSql("CREATE TEMPORARY TABLE IF NOT EXISTS source_A (\n" +
                " uuid bigint PRIMARY KEY NOT ENFORCED,\n" +
                " `name` VARCHAR(3)," +
                " _ts1 TIMESTAMP(3)\n" +
                ") WITH (\n" +
                " 'connector' = 'datagen', \n" +
                " 'fields.uuid.kind'='sequence',\n" +
                " 'fields.uuid.start'='0', \n" +
                " 'fields.uuid.end'='1000000', \n" +
                " 'rows-per-second' = '1' \n" +
                ")");
        tableEnv.executeSql("CREATE TEMPORARY TABLE IF NOT EXISTS source_B (\n" +
                " uuid bigint PRIMARY KEY NOT ENFORCED,\n" +
                " `age` int," +
                " _ts2 TIMESTAMP(3)\n" +
                ") WITH (\n" +
                " 'connector' = 'datagen', \n" +
                " 'fields.uuid.kind'='sequence',\n" +
                " 'fields.uuid.start'='0', \n" +
                " 'fields.uuid.end'='1000000', \n" +
                " 'rows-per-second' = '1' \n" +
                ")");

        //
        StatementSet statementSet = tableEnv.createStatementSet();
        String sqlText = "INSERT INTO paimon_tbl_streams(uuid, name, age, ts, dt) \n" +
                "select uuid, name, cast(null as int) as age, _ts1 as ts, date_format(_ts1,'yyyy-MM-dd') as dt from source_A \n" +
                "UNION ALL \n" +
                "select uuid, cast(null as string) as name, age, _ts2 as ts, date_format(_ts2,'yyyy-MM-dd') as dt from source_B"
                ;
        statementSet.addInsertSql(sqlText);

        statementSet.execute();
    }
}

读代码同上。

(2)读延迟

        即:从client数据落到paimon,完成与server的join,再到被Flink-paimon流读到的时间延迟;

       分钟级别延迟

2、'changelog-producer' = 'lookup'

读写同上,建表时修改参数即可: changelog-producer='lookup',与此匹配的scan-mode需要分别配置为 'latest'

lookup延迟性可能会更低,但是数据质量有待验证。

note:

经测试,在企业生产环境中full-compaction模式目前一切稳定(两条join的流QPS约3K左右,延迟2-3分钟)。

         99.9%的数据延迟在2-3分钟;

        (multiWrite的checkpoint间隔为60s时)

新一代数据湖存储技术Apache Paimon入门Demo_第8张图片

三、可能遇到的问题

1. Caused by: java.lang.ClassCastException: org.codehaus.janino.CompilerFactory cannot be cast to org.codehaus.commons.compiler.ICompilerFactory

原因:org.codehaus.janino 依赖冲突,

办法:全部exclude掉

org.codehaus.janino:*

2. Caused by: java.lang.ClassNotFoundException: org.apache.flink.util.function.SerializableFunction

原因:Flink steaming版本与Flink table版本不一致 或 确实相关依赖 (这里是paimon依赖的flink版本最低为1.14.6,与1.14.0的flink不兼容)

办法:升级Flink版本到1.14.4以上

参考Flink配置:Configuration | Apache Flink

3. Caused by: java.util.ServiceConfigurationError: org.apache.flink.table.factories.Factory: Provider org.apache.flink.table.store.connector.TableStoreManagedFactory not found

在项目的META-INF/services路径下添加 Factory 文件(这样才能匹配Flink的CatalogFactory,才能创建catalog)

4. Caused by: org.apache.flink.client.program.ProgramInvocationException: The main method caused an error: No operators defined in streaming topology. Cannot execute.

已经存在tableEnv.executeSql 或者 statementSet.execute() 时就不需要再 env.execute() 了!

5. Flink SQL不能直接使用null as,需要写成 cast(null as data_type), 如 cast(null as string);

6. 如果创建paimon分区表,必须要把分区字段放在主键中!,否则建表报错:

新一代数据湖存储技术Apache Paimon入门Demo_第9张图片

【未完待续...】

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