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Flink CDC Oracle To ES与Oracle To PG SQL和Stream方法实现 (单表、多表)

Oracle CDC Connector — CDC Connectors for Apache Flink® documentation

Flink CDC两种实现方式:

1.FlinkDataStream_CDC实现：
利用Flink_CDC自带的连接资源，如MySQLSource通过设置hostname、port、username、password、database、table、deserializer、startupOptions等参数配置
实现获取CRUD数据变化日志
2.FlinkSQL_CDC实现：
通过FlinkSQL创建虚拟表获取关键字段的变化情况并且配置hostname、port、username、password、database、table等参数可以看到具体表数据的变化过程

注意：FlinkSQL_CDC2.0仅支持Flink1.13之后的版本

Flink Table/SQL模块集成了数据库表和变化记录流（例如CDC的数据流）。作为同一事物的两面，结果是Upsert Message结构（+I表示新增、-U表示记录更新前的值、+U表示记录的更新值、-D表示删除）

两种方式对比:

1.FlinkDataStream_CDC支持多库多表的操作（优点）
2.FlinkFlinkDataStream_CDC需要自定义序列化器（缺点）
3.FlinkSQL_CDC只能单表操作（缺点）
4.FlinkSQL_CDC自动序列化（优点）

Oracle CDC 连接器

Maven依赖

<dependency>
  <groupId>com.ververica</groupId>
  <artifactId>flink-connector-oracle-cdc</artifactId>
  <!-- The dependency is available only for stable releases, SNAPSHOT dependency need build by yourself. -->
  <version>2.2.1</version>
</dependency>

下载flink-sql-connector-oracle-cdc-2.2.1.jar放到<FLINK_HOME>/lib/.

设置Oracle

您必须为 Oracle 数据库启用日志归档，并定义一个对 Debezium Oracle 连接器监控的所有数据库具有适当权限的 Oracle 用户。

对于非 CDB 数据库

  1. 启用日志归档

(1.1)。以 DBA 身份连接到数据库

linux>ORACLE_SID=SID
linux>export ORACLE_SID
linux>sqlplus /nolog
linux>CONNECT sys/password AS SYSDBA

(1.2)。启用日志归档

sql>alter system set db_recovery_file_dest_size = 10G;
sql>alter system set db_recovery_file_dest = '/opt/oracle/oradata/recovery_area' scope=spfile;
sql>shutdown immediate;
sql>startup mount;
sql>alter database archivelog;
sql>alter database open;

注意：

  • 启用日志归档需要重启数据库，尝试时注意
  • 归档日志会占用大量磁盘空间，建议定期清理过期日志

(1.3)。检查是否启用了日志归档

-- Should now "Database log mode: Archive Mode"
sql>archive log list;

注意：

必须为捕获的表或数据库启用补充日志记录，以便数据更改捕获已更改数据库行的之前状态。下面说明了如何在表/数据库级别进行配置。

-- Enable supplemental logging for a specific table:
sql>ALTER TABLE inventory.customers ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS;
-- Enable supplemental logging for database
sql>ALTER DATABASE ADD SUPPLEMENTAL LOG DATA;
  1. 创建具有权限的 Oracle 用户

(2.1)。创建表空间

sql>sqlplus sys/password@host:port/SID AS SYSDBA;
sql>CREATE TABLESPACE logminer_tbs DATAFILE '/opt/oracle/oradata/SID/logminer_tbs.dbf' SIZE 25M REUSE AUTOEXTEND ON MAXSIZE UNLIMITED;
sql>exit;

(2.2)。创建用户并授予权限

sqlplus sys/password@host:port/SID AS SYSDBA;
  CREATE USER flinkuser IDENTIFIED BY flinkpw DEFAULT TABLESPACE LOGMINER_TBS QUOTA UNLIMITED ON LOGMINER_TBS;
  GRANT CREATE SESSION TO flinkuser;
  GRANT SET CONTAINER TO flinkuser;
  GRANT SELECT ON V_$DATABASE to flinkuser;
  GRANT FLASHBACK ANY TABLE TO flinkuser;
  GRANT SELECT ANY TABLE TO flinkuser;
  GRANT SELECT_CATALOG_ROLE TO flinkuser;
  GRANT EXECUTE_CATALOG_ROLE TO flinkuser;
  GRANT SELECT ANY TRANSACTION TO flinkuser;
  GRANT LOGMINING TO flinkuser;

  GRANT CREATE TABLE TO flinkuser;
  GRANT LOCK ANY TABLE TO flinkuser;
  GRANT ALTER ANY TABLE TO flinkuser;
  GRANT CREATE SEQUENCE TO flinkuser;

  GRANT EXECUTE ON DBMS_LOGMNR TO flinkuser;
  GRANT EXECUTE ON DBMS_LOGMNR_D TO flinkuser;

  GRANT SELECT ON V_$LOG TO flinkuser;
  GRANT SELECT ON V_$LOG_HISTORY TO flinkuser;
  GRANT SELECT ON V_$LOGMNR_LOGS TO flinkuser;
  GRANT SELECT ON V_$LOGMNR_CONTENTS TO flinkuser;
  GRANT SELECT ON V_$LOGMNR_PARAMETERS TO flinkuser;
  GRANT SELECT ON V_$LOGFILE TO flinkuser;
  GRANT SELECT ON V_$ARCHIVED_LOG TO flinkuser;
  GRANT SELECT ON V_$ARCHIVE_DEST_STATUS TO flinkuser;
  exit;

连接器选项

OptionRequiredDefaultTypeDescriptionconnectorrequired(none)String指定要使用的连接器，这里应该是'oracle-cdc'.hostnamerequired(none)StringOracle 数据库服务器的 IP 地址或主机名。usernamerequired(none)String连接到 Oracle 数据库服务器时要使用的 Oracle 数据库的名称。passwordrequired(none)String连接到 Oracle 数据库服务器时使用的密码。database-namerequired(none)String要监视的 Oracle 服务器的数据库名称。schema-namerequired(none)String要监视的 Oracle 数据库的模式名称。table-namerequired(none)String要监视的 Oracle 数据库的表名。portoptional1521IntegerOracle 数据库服务器的整数端口号。scan.startup.modeoptionalinitialStringOracle CDC 消费者的可选启动模式，有效枚举为“initial”和“latest-offset”。有关更多详细信息，请参阅启动阅读位置部分。debezium.*optional(none)String将 Debezium 的属性传递给用于从 Oracle 服务器捕获数据更改的 Debezium Embedded Engine。例如：'debezium.snapshot.mode' = 'never'。查看有关
启动阅读位置

config 选项scan.startup.mode指定 Oracle CDC 使用者的启动模式。有效的枚举是：

  • initial（默认）：首次启动时对被监控的数据库表进行初始快照，并继续读取最新的binlog。
  • latest-offset：永远不要在第一次启动时对受监控的数据库表执行快照，只需从连接器启动后的更改中读取。

注意：scan.startup.mode选项的机制依赖于 Debezium 的snapshot.mode配置。所以请不要一起使用它们。如果您在 DDL 表中指定了这两个scan.startup.mode和选项，它可能会导致不起作用。**debezium.snapshot.modescan.startup.mode

Oracle CDC SQL 连接器模板:

CREATE TABLE products (
    db_name STRING METADATA FROM 'database_name' VIRTUAL,
    schema_name STRING METADATA FROM 'schema_name' VIRTUAL, 
    table_name STRING METADATA  FROM 'table_name' VIRTUAL,
    operation_ts TIMESTAMP_LTZ(3) METADATA FROM 'op_ts' VIRTUAL,
    ID INT NOT NULL,
    NAME STRING,
    DESCRIPTION STRING,
    WEIGHT DECIMAL(10, 3),
    PRIMARY KEY(id) NOT ENFORCED
) WITH (
    'connector' = 'oracle-cdc',
    'hostname' = 'Oracle_IP地址',
    'port' = '1521',
    'username' = 'flinkuser',
    'password' = 'flinkpw',
    'database-name' = 'XE',
    'schema-name' = 'inventory',
    'table-name' = 'products'
);

注意：Oracle 方言是区分大小写的，如果字段名没有被引用，它会将字段名转换为大写，Flink SQL 不会转换字段名。oracle-cdc因此对于 oracle 数据库中的物理列，我们在 Flink SQL 中定义表时应该使用其在 Oracle 中转换后的字段名称。

Oracle CDC DataStream 连接器模板

Oracle CDC 连接器也可以是 DataStream 源。您可以创建一个 SourceFunction，如下所示：

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema;
import com.ververica.cdc.connectors.oracle.OracleSource;

public class OracleSourceExample {
  public static void main(String[] args) throws Exception {
     SourceFunction<String> sourceFunction = OracleSource.<String>builder()
             .hostname(Oracle_IP地址)
             .port(1521)
             .database("XE") // monitor XE database
             .schemaList("inventory") // monitor inventory schema
             .tableList("inventory.products") // monitor products table
             .username("flinkuser")
             .password("flinkpw")
             .deserializer(new JsonDebeziumDeserializationSchema()) // converts SourceRecord to JSON String
             .build();

     StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

     env
        .addSource(sourceFunction)
        .print().setParallelism(1); // use parallelism 1 for sink to keep message ordering   
     
     env.execute();
  }
}

数据类型映射

Oracle type

Flink SQL type

NUMBER(p, s <= 0), p - s < 3

TINYINT

NUMBER(p, s <= 0), p - s < 5

SMALLINT

NUMBER(p, s <= 0), p - s < 10

INT

NUMBER(p, s <= 0), p - s < 19

BIGINT

NUMBER(p, s <= 0), 19 <= p - s <= 38

DECIMAL(p - s, 0)

NUMBER(p, s > 0)

DECIMAL(p, s)

NUMBER(p, s <= 0), p - s > 38

STRING

FLOAT
BINARY_FLOAT

FLOAT

DOUBLE PRECISION
BINARY_DOUBLE

DOUBLE

NUMBER(1)

BOOLEAN

DATE
TIMESTAMP [(p)]

TIMESTAMP [(p)] [WITHOUT TIMEZONE]

TIMESTAMP [(p)] WITH TIME ZONE

TIMESTAMP [(p)] WITH TIME ZONE

TIMESTAMP [(p)] WITH LOCAL TIME ZONE

TIMESTAMP_LTZ [(p)]

CHAR(n)
NCHAR(n)
NVARCHAR2(n)
VARCHAR(n)
VARCHAR2(n)
CLOB
NCLOB
XMLType

STRING

BLOB
ROWID

BYTES

INTERVAL DAY TO SECOND
INTERVAL YEAR TO MONTH

BIGINT

Oracle CDC SQL Oracle To ES 单表 应用实例

public class CP_LOGIN_INFO {
    private static final Logger log = LoggerFactory.getLogger(CP_LOGIN_INFO.class); //设置log

    public static void main(String[] args) throws Exception {

        EnvironmentSettings fsSettings = EnvironmentSettings.newInstance() //构建环境
                .useBlinkPlanner()
                .inStreamingMode()
                .build();

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);  //设置流的并行
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env, fsSettings); //流表环境创造
        tableEnv.getConfig().setSqlDialect(SqlDialect.DEFAULT);
        log.info("This message contains {} placeholders. {}", 2, "Yippie"); // 打印日志

        //配置检查点
        env.enableCheckpointing(180000); // 开启checkpoint 每180000ms 一次
        env.getCheckpointConfig().setMinPauseBetweenCheckpoints(50000);// 确认 checkpoints 之间的时间会进行 50000 ms
        env.getCheckpointConfig().setCheckpointTimeout(600000); //设置checkpoint的超时时间 即一次checkpoint必须在该时间内完成 不然就丢弃
        env.getCheckpointConfig().setCheckpointingMode(CheckpointingMode.EXACTLY_ONCE);//设置有且仅有一次模式 目前支持 EXACTLY_ONCE/AT_LEAST_ONCE
        env.getCheckpointConfig().setMaxConcurrentCheckpoints(1);// 设置并发checkpoint的数目
        env.getCheckpointConfig().setCheckpointStorage("hdfs:///flink-checkpoints/oracle/CP_LOGIN_INFO");  // 这个是存放到hdfs目录下

        env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);// 开启在 job 中止后仍然保留的 externalized checkpoints
        env.getCheckpointConfig().enableUnalignedCheckpoints(); // 开启实验性的 unaligned checkpoints

        String sourceDDL ="CREATE TABLE Oracle_Source (\n" +
                "     ID DECIMAL(12,0), \n" +
                "     USER_CODE STRING, \n" +
                "     LOGIN_TIME STRING, \n" +   //需要设置成STRING类型，Data或者TIMESTAMP 类型无法CAST转换
                "     OVER_TIME STRING, \n" +    //需要设置成STRING类型，Data或者TIMESTAMP 类型无法CAST转换
                "     TOKEN STRING, \n" +
                "     INSERT_TIME_HIS STRING, \n" +  //需要设置成STRING类型，Data或者TIMESTAMP 类型无法CAST转换
                "     UPDATE_TIME_HIS STRING, \n" + //需要设置成STRING类型，Data或者TIMESTAMP 类型无法CAST转换
                "     VERSION STRING, \n" +
                "     PRIMARY KEY (ID) NOT ENFORCED \n" +
                "     ) WITH (\n" +
                "     'connector' = 'oracle-cdc',\n" +
                "     'hostname' = 'Oracle_IP地址',\n" +
                "     'port' = '1521',\n" +
                "     'username' = 'xxx',\n" +
                "     'password' = 'xxx',\n" +
                "     'database-name' = 'ORCL',\n" +
                "     'schema-name' = 'XIEPEITEST',\n" +           // 注意这里要大写
                "     'table-name' = 'CP_LOGIN_INFO',\n" +
                "     'debezium.log.mining.continuous.mine'='true',\n" +   //oracle11G可以设置此参数，19c会报错
                "     'debezium.log.mining.strategy'='online_catalog',\n" + //只读oracle日志不会参数新的归档日志文件
                "     'debezium.log.mining.sleep.time.increment.ms'='5000',\n" +  //设置睡眠时间可以降低Oracle连接进行内存上涨速度
                "     'debezium.log.mining.batch.size.max'='50000000000000',\n" + //如果此值太小会造成SCN追不上,而导致任务失败
                "     'debezium.log.mining.batch.size.min'='10000',\n" +
                "     'debezium.log.mining.session.max.ms'='1200000',\n" +    //设置会话连接时长，如果您的重做日志不经常切换，您可以通过指定 Oracle 切换日志的频率来避免 ORA-04036 错误
                "     'debezium.database.tablename.case.insensitive'='false',\n" +  //关闭大小写
                "     'scan.startup.mode' = 'initial' \n" +             //全量模式，先全量后自动记录增量
                "     )";

        // 创建一张用于输出的表   时间字段转换成BIGINT （CAST）
        String sinkDDL = "CREATE TABLE SinkTable (\n" +
                "     ID DECIMAL(12,0), \n" +
                "     USER_CODE STRING, \n" +
                "     LOGIN_TIME BIGINT, \n" +    //根据业务要求 需要设置成BIGINT类型 es落盘会自动创建对应的字段与相应的类型
                "     OVER_TIME BIGINT, \n" +     //根据业务要求 需要设置成BIGINT类型 es落盘会自动创建对应的字段与相应的类型
                "     TOKEN STRING, \n" +
                "     INSERT_TIME_HIS BIGINT, \n" +   //根据业务要求 需要设置成BIGINT类型 es落盘会自动创建对应的字段与相应的类型
                "     UPDATE_TIME_HIS BIGINT, \n" +   //根据业务要求 需要设置成BIGINT类型 es落盘会自动创建对应的字段与相应的类型
                "     VERSION STRING, \n" +
                "     PRIMARY KEY (ID) NOT ENFORCED \n" +
                ") WITH (\n" +
                " 'connector' = 'elasticsearch-7',\n" +
                " 'hosts' = 'http://ES_IP地址:9200',\n" +
                " 'format' = 'json',\n" +  //一定要加
                " 'index' = 'cp_login_info_test',\n" +
                " 'username' = 'elastic',\n" +
                " 'password' = 'xxx',\n" +
                " 'failure-handler' = 'ignore',\n" +
                " 'sink.flush-on-checkpoint' = 'true' ,\n"+
                " 'sink.bulk-flush.max-actions' = '20000' ,\n"+
                " 'sink.bulk-flush.max-size' = '2mb' ,\n"+
                " 'sink.bulk-flush.interval' = '1000ms' ,\n"+
                " 'sink.bulk-flush.backoff.strategy' = 'CONSTANT',\n"+
                " 'sink.bulk-flush.backoff.max-retries' = '3',\n"+
                " 'connection.max-retry-timeout' = '3153600000000',\n"+  //设置es连接时间，太短的话会自动断连
                " 'sink.bulk-flush.backoff.delay' = '100ms'\n"+
                ")";

        String transformSQL =
                " INSERT INTO SinkTable  SELECT ID,\n" +
                        "USER_CODE,\n" +
                        "(CAST(LOGIN_TIME AS BIGINT) - 8 * 60 * 60 * 1000 ) as LOGIN_TIME,\n" + //类型转换 - 8小时 （CAST（字段 AS 类型 ）-时区差） as 新字段名或落盘字段名
                        "(CAST(OVER_TIME  AS BIGINT) - 8 * 60 * 60 * 1000 ) as OVER_TIME,\n" +  //类型转换 - 8小时 （CAST（字段 AS 类型 ）-时区差） as 新字段名或落盘字段名

                        "TOKEN,\n" +
                        "(CAST(INSERT_TIME_HIS AS BIGINT) - 8 * 60 * 60 * 1000 ) as INSERT_TIME_HIS,\n" +  //类型转换 - 8小时 （CAST（字段 AS 类型 ）-时区差） as 新字段名或落盘字段名
                        "(CAST(UPDATE_TIME_HIS AS BIGINT)  - 8 * 60 * 60 * 1000 ) as UPDATE_TIME_HIS,\n" +  //类型转换 - 8小时 （CAST（字段 AS 类型 ）-时区差） as 新字段名或落盘字段名
                        "VERSION FROM  Oracle_Source " ;

        //执行source表ddl
        tableEnv.executeSql(sourceDDL);

        //执行sink表ddl
        tableEnv.executeSql(sinkDDL);

        //执行逻辑sql语句
        TableResult tableResult = tableEnv.executeSql(transformSQL);
        tableResult.print();
        env.execute();

    }
}

Oracle CDC DataStream 应用实例

  1. 编写运行脚本
public class OracleSourceExample2 {

    //自定义source 源 oracle
    public static void main(String[] args) throws Exception {

        //构建source
        SourceFunction<String> sourceFunction = OracleSource.<String>builder()
                .hostname("Oracle_IP地址")
                .port(1521)
                .database("ORA19C") // monitor XE database
                .schemaList("FLINKUSER") // monitor inventory schema
                .tableList("FLINKUSER.T_Oracle_Score") // monitor products table 如果这个注销掉的话，就会监控所有表
                .username("flinkuser")
                .password("flinkpw")
                .deserializer(new CustomerDeserialization())
                //.deserializer(new JsonDebeziumDeserializationSchema())
                .build();

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); //设置flink 执行环境
        env.setParallelism(1); // use parallelism 1 for sink to keep message ordering
        DataStreamSource<String> stream = env.addSource(sourceFunction); //添加流

    stream.print(); //打印流

        //定义ES服务器地址列表
        List<HttpHost> httpHosts = new ArrayList<>();
        httpHosts.add(new HttpHost("ES_IP地址", 9200, "http"));

// 设置ES sink方法
        ElasticsearchSink.Builder<String> esSinkBuilder = new ElasticsearchSink.Builder<>(
                httpHosts,
                new ElasticsearchSinkFunction<String>() {
                    public IndexRequest createIndexRequest(String element) { //插入数据没有的话进行创建索引
                        Map<String, String> json = new HashMap<>();
                        //调用类解析数据
                        CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element,CustomerDeserialization.AfterBean.class);
                        CustomerDeserialization Data = JSON.parseObject(element,CustomerDeserialization.class);

                        System.out.println("===============");
                        System.out.println(String.valueOf(Data.getAfter().getID()));
                        json.put("ID", String.valueOf(Data.getAfter().getID()));
                        json.put("NAME",Data.getAfter().getNAME());

                        return Requests.indexRequest()
                                .index("testES")
                                .id(String.valueOf(Data.getAfter().getID())) //必须插入id 以后才能做更新和删除
                                .source(json);

                    }

                    public UpdateRequest updateIndexRequest(String element)throws IOException { //更新数据

                        //设置表的index和type,必须设置id才能update
                        CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element,CustomerDeserialization.AfterBean.class);
                        CustomerDeserialization Data = JSON.parseObject(element,CustomerDeserialization.class);
                        UpdateRequest updateRequest=new UpdateRequest();
                        System.out.println("*******:"+Data.getAfter().getNAME());
                        System.out.println(element);
                        String id = String.valueOf(Data.getAfter().getID());
                        String data = Data.getAfter().getNAME();
                        System.out.println(id);
                        updateRequest
                                .index("testES").upsert()
                                .id(id) //指定索引id
                               .doc(XContentFactory.jsonBuilder().startObject().field("NAME",data).endObject()); //指定数据
                        return  updateRequest;
                    }

                    private  DeleteRequest deleteDocumentById(String element) { //删除数据
                        CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element,CustomerDeserialization.AfterBean.class);
                        CustomerDeserialization Data = JSON.parseObject(element,CustomerDeserialization.class);
                         DeleteRequest deleteRequest = new DeleteRequest();
                        return deleteRequest
                                .index("testES")
                                .id(String.valueOf(Data.getBefore().getID())); //根据id删除数据
                    }

                    @Override
                    public void process(String element, RuntimeContext ctx, RequestIndexer indexer) {
                        //根据类解析
                        CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element,CustomerDeserialization.AfterBean.class);
                        CustomerDeserialization Data = JSON.parseObject(element,CustomerDeserialization.class);
                        //判断接收的流做增删改
                        if (Data.getAfter().getID() !=null && Data.getBefore().getID() == null) {
                            System.out.println("*****插入******");
                            indexer.add(createIndexRequest(element));
                        } else  if (Data.getAfter().getID() !=null && Data.getBefore().getID() !=null){
                            try {
                                System.out.println("*****更新******");
                                indexer.add(updateIndexRequest(element));
                            } catch (IOException e) {
                                e.printStackTrace();
                            }
                        } else  if (Data.getAfter().getID() ==null && Data.getBefore().getID() !=null) {
                            System.out.println("*****删除******");
                            indexer.add(deleteDocumentById(element));
                        }
                    }
                }
        );

       //批量请求的配置； 这指示接收器在每个元素之后发出，否则它们将被缓冲
        //刷新前缓冲的最大动作量
        esSinkBuilder.setBulkFlushMaxActions(1);
        //刷新前缓冲区的最大数据大小（以MB为单位）
        esSinkBuilder.setBulkFlushMaxSizeMb(500);
        //论缓冲操作的数量或大小如何都要刷新的时间间隔
        esSinkBuilder.setBulkFlushInterval(501);
   
        stream.addSink(esSinkBuilder.build());
        env.execute();

    }
}
  1. 2.编写反序列化
public class CustomerDeserialization implements DebeziumDeserializationSchema<String> {

    /**
     * 封装的数据格式
     * {
     * "database":"",
     * "tableName":"",
     * "before":{"id":"","tm_name":""....},
     * "after":{"id":"","tm_name":""....},
     * "type":"c u d",
     * //"ts":xxxxxxxxxxxxx
     * }
     */
    @Override
    public void deserialize(SourceRecord sourceRecord, Collector<String> collector) throws Exception {

        //1.创建JSON对象用于存储最终数据
        JSONObject result = new JSONObject();

        //2.获取库名&表名
        String topic = sourceRecord.topic();
        String[] fields = topic.split("\\.");
        String database = fields[1];
        String tableName = fields[2];

        Struct value = (Struct) sourceRecord.value();
        //3.获取"before"数据
        Struct before = value.getStruct("before");
        JSONObject beforeJson = new JSONObject();
        if (before != null) {
            Schema beforeSchema = before.schema();
            List<Field> beforeFields = beforeSchema.fields();
            for (Field field : beforeFields) {
                Object beforeValue = before.get(field);
                beforeJson.put(field.name(), beforeValue);
            }
        }

        //4.获取"after"数据
        Struct after = value.getStruct("after");
        JSONObject afterJson = new JSONObject();
        if (after != null) {
            Schema afterSchema = after.schema();
            List<Field> afterFields = afterSchema.fields();
            for (Field field : afterFields) {
                Object afterValue = after.get(field);
                afterJson.put(field.name(), afterValue);
            }
        }

        //5.获取操作类型  CREATE UPDATE DELETE
        Envelope.Operation operation = Envelope.operationFor(sourceRecord);
        String type = operation.toString().toLowerCase();
        if ("create".equals(type)) {
            type = "insert";
        }

        //6.将字段写入JSON对象
        result.put("database", database);
        result.put("tableName", tableName);
        result.put("before", beforeJson);
        result.put("after", afterJson);
        result.put("type", type);

        //7.输出数据
        collector.collect(result.toJSONString());

    }

    @Override
    public TypeInformation<String> getProducedType() {
        return BasicTypeInfo.STRING_TYPE_INFO;
    }

    private AfterBean after;
    private  AfterBean  before;

    public AfterBean getAfter() {
        return after;
    }
    public void setAfter(AfterBean after) {
        this.after = after;
    }

    public AfterBean getBefore() {
        return before;
    }

    public void setBefore(AfterBean before) {
        this.before = before;
    }

    private String type;

    public String getType() {
        return type;
    }

    public void setType(String type) {
        this.type = type;
    }

    public static class AfterBean {

        private Long ID;
        private String NAME;

        public Long getID() {
            return ID;
        }

        public void setID(Long ID) {
            this.ID = ID;
        }

        public void setNAME(String NAME) {
            this.NAME = NAME;
        }

        public String getNAME() {
            return NAME;
        }
    }
}

Oracle CDC SQL Oracle TO ES 多表 应用实例

1.编写运行脚本

public class OracleSourceExample2 {
    public static void main(String[] args) throws Exception {
        //构建source
        SourceFunction<String> sourceFunction = OracleSource.<String>builder()
                .hostname("Oracle_IP地址")
                .port(1521)
                .database("ORA19C") // monitor XE database
                .schemaList("FLINKUSER") // monitor inventory schema
                .tableList("FLINKUSER.T_Oracle_Score,FLINKUSER.T_Oracle_Score2") // monitor products table 如果这个注销掉的话，就会监控所有表
                .username("flinkuser")
                .password("flinkpw")
                .deserializer(new DataStreamMoreOracleToES.CustomerDeserialization()) //自定义反序列化器
                .build();
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); //设置flink 执行环境
        env.setParallelism(1); // use parallelism 1 for sink to keep message ordering
        DataStreamSource<String> stream = env.addSource(sourceFunction);

        // 定义旁路输出的tag，旁路输出时会绑定该tag。这里需要定义tag的名称。
        final OutputTag<String> sideOutputTag1 = new OutputTag<String>("sideOutput1") {};
        final OutputTag<String> sideOutputTag2 = new OutputTag<String>("sideOutput2") {};

        // 处理数据时，输出到一个或多个侧输出流 ，分流操作
        SingleOutputStreamOperator<String> mainDataStream = stream
                .process(new ProcessFunction<String,String>() {

                             @Override
                             public void processElement(String element, Context context, Collector<String> collector) throws Exception {
                                 DataStreamMoreOracleToES.CustomerDeserialization.AfterBean afterBean = JSON.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.AfterBean.class);
                                 DataStreamMoreOracleToES.CustomerDeserialization Data = JSON.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.class);
                                 String seasonType = Data.getTableName();
                                 switch (seasonType){
                                     case "T_ORACLE_SCORE":
                                         context.output(sideOutputTag1,element);
                                         break;
                                     case "T_ORACLE_SCORE2":
                                         context.output(sideOutputTag2,element);
                                         break;

                             }
                             }
                         });

        DataStream<String> T_ORACLE_SCORE = mainDataStream.getSideOutput(sideOutputTag1); //设置标签
        SingleOutputStreamOperator<JSONObject> table1  = T_ORACLE_SCORE.map(JSON::parseObject)
                .assignTimestampsAndWatermarks(
                WatermarkStrategy
                        .<JSONObject>forMonotonousTimestamps()
                        .withTimestampAssigner(new SerializableTimestampAssigner<JSONObject>() {
                            @Override
                            public long extractTimestamp(JSONObject o, long l) {
                                return o.getLong("ts_ms");
                            }
                        }));

        DataStream<String> T_ORACLE_SCORE2 = mainDataStream.getSideOutput(sideOutputTag2);//设置标签
        SingleOutputStreamOperator<JSONObject> table2  = T_ORACLE_SCORE2.map(JSON::parseObject)
        .assignTimestampsAndWatermarks(
                WatermarkStrategy
                        .<JSONObject>forMonotonousTimestamps()
                        .withTimestampAssigner(new SerializableTimestampAssigner<JSONObject>() {
                            @Override
                            public long extractTimestamp(JSONObject o, long l) {
                                return o.getLong("ts_ms");
                            }
                        }));

          table1.print("表1:");
          table2.print("表2:");

          //设置intervalJoin 指定时间内进行join，数据缺失没有的会丢弃 不join上
        SingleOutputStreamOperator <DataStreamMoreOracleToES.CustomerDeserialization.WideOrder.AfterBean > wideOrderDS = table1
                .keyBy(jsonObject -> jsonObject.getJSONObject("after").getLong("ID"))
                .intervalJoin(table2.keyBy(jsonObject -> jsonObject.getJSONObject("after").getLong("ID")))
                .between(Time.milliseconds(-100000), Time.milliseconds(100000))
                .process(new ProcessJoinFunction<JSONObject, JSONObject, CustomerDeserialization.WideOrder.AfterBean >() {
                    @Override
                    public void processElement(JSONObject ord, JSONObject cust, Context context, Collector<DataStreamMoreOracleToES.CustomerDeserialization.WideOrder.AfterBean > collector) throws Exception {
                        DataStreamMoreOracleToES.CustomerDeserialization.WideOrder.AfterBean wideOrder = new DataStreamMoreOracleToES.CustomerDeserialization.WideOrder.AfterBean();

                        JSONObject ordAfter = ord.getJSONObject("after");
                        JSONObject custAfter = cust.getJSONObject("after");
                        wideOrder.setID(ordAfter.getLong("ID"));
                        wideOrder.setNAME(ordAfter.getString("NAME"));
                        wideOrder.setAGE(custAfter.getLong("AGE"));

                        JSONObject ordBefore = ord.getJSONObject("before");
                        JSONObject custBefore = cust.getJSONObject("before");
                        wideOrder.setBrforeID(ordBefore.getLong("ID"));

                        collector.collect(wideOrder);

                    }
                });

        SingleOutputStreamOperator<String> stringWideOrderDS = wideOrderDS.map(wideOrder -> wideOrder.toString());
        stringWideOrderDS.print();

        //定义ES服务器地址列表
        List<HttpHost> httpHosts = new ArrayList<>();
        httpHosts.add(new HttpHost("ES_IP地址", 9200, "http"));

    // 设置ES sink方法
        ElasticsearchSink.Builder<String> esSinkBuilder = new ElasticsearchSink.Builder<>(
                httpHosts,
                new ElasticsearchSinkFunction<String>() {

                    public IndexRequest createIndexRequest(String element) {

                        Map<String, String> json = new HashMap<>();

                        DataStreamMoreOracleToES.CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.AfterBean.class);
                        DataStreamMoreOracleToES.CustomerDeserialization Data = JSON.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.class);

                        System.out.println("===============");
                        System.out.println(String.valueOf(Data.getAfter().getID()));

                        json.put("ID", String.valueOf(Data.getAfter().getID()));
                        json.put("NAME",Data.getAfter().getNAME());
                        json.put("AGE", String.valueOf(Data.getAfter().getAGE()));

                        return Requests.indexRequest()
                                .index("testES")
                                .id(String.valueOf(Data.getAfter().getID()))
                                .source(json);
                    }
                    public UpdateRequest updateIndexRequest(String element)throws IOException {

                        //设置表的index和type,必须设置id才能update

                        DataStreamMoreOracleToES.CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.AfterBean.class);
                        DataStreamMoreOracleToES.CustomerDeserialization Data = JSON.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.class);

                        UpdateRequest updateRequest=new UpdateRequest();

                        //设置表的index和type,必须设置id才能update
                        System.out.println("*******:"+Data.getAfter().getNAME());
                        System.out.println(element);
                        String id = String.valueOf(Data.getAfter().getID());
                        String data = Data.getAfter().getNAME();
                        System.out.println(id);
                        updateRequest
                                .index("testES").upsert()
                                .id(id)
                                .doc(XContentFactory.jsonBuilder().startObject().field("NAME",data).endObject());
                        return  updateRequest;
                    }

                    private  DeleteRequest deleteDocumentById(String element) {
                        DataStreamMoreOracleToES.CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.AfterBean.class);
                        DataStreamMoreOracleToES.CustomerDeserialization Data = JSON.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.class);
                         DeleteRequest deleteRequest = new DeleteRequest();

                        return deleteRequest
                                .index("testES")
                                .id(String.valueOf(Data.getBefore().getID()));

                    }

                    @Override
                    public void process(String element, RuntimeContext ctx, RequestIndexer indexer) {
                        DataStreamMoreOracleToES.CustomerDeserialization.AfterBean afterBean = JSONObject.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.AfterBean.class);
                        DataStreamMoreOracleToES.CustomerDeserialization Data = JSON.parseObject(element, DataStreamMoreOracleToES.CustomerDeserialization.class);

                        if (Data.getAfter().getID() !=null ) {
                            System.out.println("*****插入******");
                            System.out.println("***:"+element);
                            indexer.add(createIndexRequest(element));
                        } else  if (Data.getAfter().getID() !=null && Data.getBefore().getID() !=null){
                            try {
                                System.out.println("*****更新******");

                                indexer.add(updateIndexRequest(element));
                            } catch (IOException e) {
                                e.printStackTrace();
                            }

                        } else  if (Data.getAfter().getID() ==null && Data.getBefore().getID() !=null) {
                            System.out.println("*****删除******");
                            indexer.add(deleteDocumentById(element));
                        }

                    }
                }
        );

       //批量请求的配置； 这指示接收器在每个元素之后发出，否则它们将被缓冲
        //刷新前缓冲的最大动作量
        esSinkBuilder.setBulkFlushMaxActions(1);
        //刷新前缓冲区的最大数据大小（以MB为单位）
        esSinkBuilder.setBulkFlushMaxSizeMb(500);
        //论缓冲操作的数量或大小如何都要刷新的时间间隔
        esSinkBuilder.setBulkFlushInterval(501);

        env.execute();
    }

}

2.编写反序列化

public class CustomerDeserialization implements DebeziumDeserializationSchema<String> {

    /**
     * 封装的数据格式
     * {
     * "database":"",
     * "tableName":"",
     * "before":{"id":"","tm_name":""....},
     * "after":{"id":"","tm_name":""....},
     * "type":"c u d",
     * //"ts":156456135615
     * }
     */
    @Override
    public void deserialize(SourceRecord sourceRecord, Collector<String> collector) throws Exception {

        //1.创建JSON对象用于存储最终数据
        JSONObject result = new JSONObject();

        //2.获取库名&表名
        String topic = sourceRecord.topic();
        String[] fields = topic.split("\\.");
        String database = fields[1];
        String tableName = fields[2];
        //String ts_ms = fields[2];

        Struct value = (Struct) sourceRecord.value();
        //3.获取"before"数据
        Struct before = value.getStruct("before");

        JSONObject beforeJson = new JSONObject();
        if (before != null) {
            Schema beforeSchema = before.schema();
            List<Field> beforeFields = beforeSchema.fields();
            for (Field field : beforeFields) {
                Object beforeValue = before.get(field);
                beforeJson.put(field.name(), beforeValue);
            }
        }

        //4.获取"after"数据
        Struct after = value.getStruct("after");
        JSONObject afterJson = new JSONObject();
        if (after != null) {
            Schema afterSchema = after.schema();
            List<Field> afterFields = afterSchema.fields();
            for (Field field : afterFields) {
                Object afterValue = after.get(field);
                afterJson.put(field.name(), afterValue);
            }
        }
        //4.获取timestamp
        long ts = (long) value.get("ts_ms");

        //5.获取操作类型  CREATE UPDATE DELETE
        Envelope.Operation operation = Envelope.operationFor(sourceRecord);
        String type = operation.toString().toLowerCase();
        if ("create".equals(type)) {
            type = "insert";
        }

        //6.将字段写入JSON对象
        result.put("database", database);
        result.put("tableName", tableName);
        result.put("before", beforeJson);
        result.put("after", afterJson);
        result.put("type", type);
        result.put("ts_ms",ts);

        //7.输出数据
        collector.collect(result.toJSONString());

    }

    @Override
    public TypeInformation<String> getProducedType() {
        return BasicTypeInfo.STRING_TYPE_INFO;
    }

    private AfterBean after;
    private  AfterBean  before;

    public AfterBean getAfter() {
        return after;
    }
    public void setAfter(AfterBean after) {
        this.after = after;
    }

    public AfterBean getBefore() {
        return before;
    }
    public void setBefore(AfterBean before) {
        this.before = before;
    }

    private String type;
    public String getType() {
        return type;
    }
    public void setType(String type) {
        this.type = type;
    }

    private String tableName;

    public String getTableName() {
        return tableName;
    }

    public void setTableName(String tableName) {
        this.tableName = tableName;
    }

    public static class AfterBean {
        /**
         * EMPNO : zhangsan
         */
        private Long ID;
        private String NAME;
        private Long AGE;

        public Long getID() {
            return ID;
        }

        public void setID(Long ID) {
            this.ID = ID;
        }

        public void setNAME(String NAME) {
            this.NAME = NAME;
        }

        public String getNAME() {
            return NAME;
        }
        public Long getAGE() {
            return AGE;
        }

        public void setAGE(Long AGE) {
            this.AGE = AGE;
        }
    }

    //多表

    public static class WideOrder  {
        private AfterBean after;
        private  AfterBean  before;
        public AfterBean getAfter() {
            return after;
        }
        public void setAfter(AfterBean after) {
            this.after = after;
        }

        public AfterBean getBefore() {
            return before;
        }
        public void setBefore(AfterBean before) {
            this.before = before;
        }

        public static class AfterBean {

            private Long ID;
            private Long BrforeID;
            private String NAME;
            private Long AGE;
            private Timestamp ts;  // come from orders-stream
            public Long getID() {
                return ID;
            }

            public String getNAME() {
                return NAME;
            }

            public Long getAGE() {
                return AGE;
            }

            public Timestamp getTs() {
                return ts;
            }

            public void setID(Long ID) {
                this.ID = ID;
            }

            public void setNAME(String NAME) {
                this.NAME = NAME;
            }

            public void setAGE(Long AGE) {
                this.AGE = AGE;
            }

            public void setTs(Timestamp ts) {
                this.ts = ts;
            }

            public Long getBrforeID() {
                return BrforeID;
            }

            public void setBrforeID(Long brforeID) {
                BrforeID = brforeID;
            }

            @Override
            public String toString() {
                JSONObject afterjsonObject = new JSONObject();
                afterjsonObject.put("ID",ID);
                afterjsonObject.put("NAME",NAME);
                afterjsonObject.put("AGE",AGE);
                String after = afterjsonObject.toJSONString();

                JSONObject beforejsonObject = new JSONObject();
                beforejsonObject.put("ID",BrforeID);
                String before = beforejsonObject.toJSONString();

                return "{\"before\":" +before+","+"\"after\":"+after+ '}';
            }

        }

        public WideOrder() {}
    }
}

Oracle CDC SQL Oracle TO PG 单表 应用实例

1.编写运行脚本

public class OracleSourceExample {
    //自定义source 源 oracle

    public static void main(String[] args) throws Exception {
        //构建source
        SourceFunction<String> sourceFunction = OracleSource.<String>builder()
                .hostname("Oracle_IP地址")
                .port(1521)
                .database("ORA19C") // monitor XE database
                .schemaList("FLINKUSER") // monitor inventory schema
                .tableList("FLINKUSER.T_Oracle_Score") // monitor products table 如果这个注销掉的话，就会监控所有表
                .username("flinkuser")
                .password("flinkpw")
                //.deserializer(new JsonDebeziumDeserializationSchema()) // converts SourceRecord to JSON String
                 .deserializer(new CustomerDeserialization())
                .build();

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); //设置flink 执行环境
        env.setParallelism(1); // use parallelism 1 for sink to keep message ordering
        DataStreamSource<String> stream = env.addSource(sourceFunction);
         stream.print(); //打印流
        stream.addSink(new MyJdbcSink()); //添加 落盘

        env.execute();
    }

    // 实现自定义的SinkFunction
    public static class MyJdbcSink extends RichSinkFunction<String> {
        // 声明连接和预编译语句
        Connection connection = null;
        PreparedStatement insertStmt = null;
        PreparedStatement updateStmt = null;
        PreparedStatement deleteStmt = null;

        @Override
        public void open(Configuration parameters) throws Exception {
            Class.forName("org.postgresql.Driver");//加载数据库驱动
            connection = DriverManager.getConnection("jdbc:postgresql://PG_IP地址/postgres", "postgres", "postgres");
            insertStmt = connection.prepareStatement("insert into t_pg_sink values (?,?)");
            updateStmt = connection.prepareStatement("update t_pg_sink set name = ? where id = ?");
            deleteStmt = connection.prepareStatement("delete from t_pg_sink where id = ?");
        }

        // 每来一条数据，调用连接，执行sql
        @Override
        public void invoke(String value, Context context) throws Exception {
            // 直接执行更新语句，如果没有更新那么就插入
            CustomerDeserialization.AfterBean afterBean = com.alibaba.fastjson.JSON.parseObject(value, CustomerDeserialization.AfterBean.class);
            CustomerDeserialization Type = JSON.parseObject(value, CustomerDeserialization.class);

            System.out.println("***");
                if (Type.getAfter().getID() == null  && Type.getBefore().getID() !=null ) {

                    System.out.println("删除");
                    deleteStmt.setInt(1,Integer.parseInt(Type.getBefore().getID()));
                    deleteStmt.execute(); //执行删除
                } else  {
                    updateStmt.setString(1, Type.getAfter().getNAME());
                    updateStmt.setInt(2, Integer.parseInt(Type.getAfter().getID()));
                    updateStmt.execute(); //执行更新
                    if (updateStmt.getUpdateCount() == 0) {
                        insertStmt.setInt(1, Integer.parseInt(Type.getAfter().getID()));
                        insertStmt.setString(2, Type.getAfter().getNAME());
                        insertStmt.execute(); //执行插入
                    }
                }
        }

        @Override
        public void close() throws Exception {
            deleteStmt.close();
            insertStmt.close();
            updateStmt.close();
            connection.close();
        }
    }
}

2.编写反序列化

public class CustomerDeserialization implements DebeziumDeserializationSchema<String> {

    /**
     * 封装的数据格式
     * {
     * "database":"",
     * "tableName":"",
     * "before":{"id":"","tm_name":""....},
     * "after":{"id":"","tm_name":""....},
     * "type":"c u d",
     * //"ts":156456135615
     * }
     */
    @Override
    public void deserialize(SourceRecord sourceRecord, Collector<String> collector) throws Exception {

        //1.创建JSON对象用于存储最终数据
        JSONObject result = new JSONObject();

        //2.获取库名&表名
        String topic = sourceRecord.topic();
        String[] fields = topic.split("\\.");
        String database = fields[1];
        String tableName = fields[2];

        Struct value = (Struct) sourceRecord.value();
        //3.获取"before"数据
        Struct before = value.getStruct("before");
        JSONObject beforeJson = new JSONObject();
        if (before != null) {
            Schema beforeSchema = before.schema();
            List<Field> beforeFields = beforeSchema.fields();
            for (Field field : beforeFields) {
                Object beforeValue = before.get(field);
                beforeJson.put(field.name(), beforeValue);
            }
        }

        //4.获取"after"数据
        Struct after = value.getStruct("after");
        JSONObject afterJson = new JSONObject();
        if (after != null) {
            Schema afterSchema = after.schema();
            List<Field> afterFields = afterSchema.fields();
            for (Field field : afterFields) {
                Object afterValue = after.get(field);
                afterJson.put(field.name(), afterValue);
            }
        }

        //5.获取操作类型  CREATE UPDATE DELETE
        Envelope.Operation operation = Envelope.operationFor(sourceRecord);
        String type = operation.toString().toLowerCase();
        if ("create".equals(type)) {
            type = "insert";
        }

        //6.将字段写入JSON对象
        result.put("database", database);
        result.put("tableName", tableName);
        result.put("before", beforeJson);
        result.put("after", afterJson);
        result.put("type", type);

        //7.输出数据
        collector.collect(result.toJSONString());

    }

    @Override
    public TypeInformation<String> getProducedType() {
        return BasicTypeInfo.STRING_TYPE_INFO;
    }

    private AfterBean after;
    private  AfterBean  before;

    public AfterBean getAfter() {
        return after;
    }
    public void setAfter(AfterBean after) {
        this.after = after;
    }

    public AfterBean getBefore() {
        return before;
    }

    public void setBefore(AfterBean before) {
        this.before = before;
    }

    private String type;

    public String getType() {
        return type;
    }

    public void setType(String type) {
        this.type = type;
    }

    public static class AfterBean {

        private String ID;
        private String NAME;

        public String getID() {
            return ID;
        }

        public void setID(String ID) {
            this.ID = ID;
        }

        public void setNAME(String NAME) {
            this.NAME = NAME;
        }

        public String getNAME() {
            return NAME;
        }
    }
}
标签： 数据库 oracle flink
本文转载自: https://blog.csdn.net/Mogeko1/article/details/128704340
版权归原作者 房石阳明i 所有， 如有侵权，请联系我们删除。
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