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新一代数据湖存储技术Apache Paimon入门Demo

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。


    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

  1. 需要先下载jar包，并添加至flink的lib中；

  2. 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。

  1. 通过 localhost:8081 查看 Flink UI

  1. 查看filesystem数据、元数据文件

2、IDEA中跑Paimon Demo

pom依赖：

        <dependency>
            <groupId>org.apache.paimon</groupId>
            <artifactId>paimon-flink-1.14</artifactId>
            <version>0.4-SNAPSHOT</version>
        </dependency>

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

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：

   如果只有一个流，上述代码完全没有问题【仅作为write demo一个流即可】，两个流会出现“写冲突”问题！

如下：

    使用了官网的方法：Dedicated Compaction Job，似乎并没有奏效，至于解决方法请看下文 “**二、进阶：本地（IDEA）多流拼接测试**”；

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<Row> dataStream = ((StreamTableEnvironment) tableEnv).toChangelogStream(table);
        // todo : doesn't support consuming update and delete changes which is produced by node TableSourceScan
        // DataStream<Row> 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<Row> dataStream = ((StreamTableEnvironment) tableEnv)
                .toChangelogStream(table, Schema.newBuilder().primaryKey("dt","uuid").build(), ChangelogMode.upsert())
                .filter(new FilterFunction<Row>() {
                    @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：

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）

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

<exclude>org.codehaus.janino:*</exclude>

  1. 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

  1. 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）

  1. 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！

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

  2. 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：

四、展望

如果有数据格式：

**主键 stream_client stream_server ts **

1001 null a 1

1001 A null 2

1001 B null 3

按照paimon官方的实现，使用主键表的partial update进行多流拼接会被拼接为如下结果：

1001 B a 3；

  即：**主键会被去重**（取每个流里边最新的一条），如果想要保留   stream_client  的全部数据，官方源码实现不了，需要进行改造！

  我们已经改造并实现了非去重的效果，后续出一篇专门的文章阐述一下改造思路和方法。

想象：

  stream_client为客户端数据，请求一次服务之后，可以上下滑动屏幕（或者进入后回退），使某个商品产生多次曝光（但不会多次请求server端）；此时 client 端产生了多条数据，server端只有一条数据。但是，client端多次的曝光/点击是可以反应用户对某个商品的感兴趣程度的，是有意义的数据，不应该被去重掉！

【未完待续...】

标签： flink 大数据 开源
本文转载自: https://blog.csdn.net/LutherK/article/details/130775956
版权归原作者 Leonardo_KY 所有， 如有侵权，请联系我们删除。
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