如何使用Flink CDC實(shí)現(xiàn) Oracle數(shù)據(jù)庫數(shù)據(jù)同步
前言
Flink CDC 是一個(gè)基于流的數(shù)據(jù)集成工具,旨在為用戶提供一套功能更加全面的編程接口(API)。 該工具使得用戶能夠以 YAML 配置文件的形式實(shí)現(xiàn)數(shù)據(jù)庫同步,同時(shí)也提供了Flink CDC Source Connector API。 Flink CDC 在任務(wù)提交過程中進(jìn)行了優(yōu)化,并且增加了一些高級特性,如表結(jié)構(gòu)變更自動(dòng)同步(Schema Evolution)、數(shù)據(jù)轉(zhuǎn)換(Data Transformation)、整庫同步(Full Database Synchronization)以及 精確一次(Exactly-once)語義。
本文通過flink-connector-oracle-cdc來實(shí)現(xiàn)Oracle數(shù)據(jù)庫的數(shù)據(jù)同步。
一、開啟歸檔日志
1)數(shù)據(jù)庫服務(wù)器終端,使用sysdba角色連接數(shù)據(jù)庫
sqlplus / as sysdba 或 sqlplus /nolog CONNECT sys/password AS SYSDBA;
2)檢查歸檔日志是否開啟
archive log list;
(“Database log mode: No Archive Mode”,日志歸檔未開啟)
(“Database log mode: Archive Mode”,日志歸檔已開啟)
3)啟用歸檔日志
alter system set db_recovery_file_dest_size = 10G; alter system set db_recovery_file_dest = '/opt/oracle/oradata/recovery_area' scope=spfile; shutdown immediate; startup mount; alter database archivelog; alter database open;
注意:
啟用歸檔日志需要重啟數(shù)據(jù)庫。
歸檔日志會占用大量的磁盤空間,應(yīng)定期清除過期的日志文件
4)啟動(dòng)完成后重新執(zhí)行 archive log list; 查看歸檔打開狀態(tài)
二、創(chuàng)建flinkcdc專屬用戶
2.1 對于Oracle 非CDB數(shù)據(jù)庫,執(zhí)行如下sql
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_$DATABASE to flinkuser; GRANT FLASHBACK ANY TABLE TO flinkuser; GRANT SELECT ANY TABLE TO flinkuser; GRANT SELECT_CATALOG_ROLE TO flinkuser; GRANT EXECUTE_CATALOG_ROLE TO flinkuser; GRANT SELECT ANY TRANSACTION TO flinkuser; GRANT LOGMINING TO flinkuser; GRANT ANALYZE ANY TO flinkuser; GRANT CREATE TABLE TO flinkuser; -- need not to execute if set scan.incremental.snapshot.enabled=true(default) GRANT LOCK ANY TABLE TO flinkuser; GRANT ALTER ANY TABLE TO flinkuser; GRANT CREATE SEQUENCE TO flinkuser; GRANT EXECUTE ON DBMS_LOGMNR TO flinkuser; GRANT EXECUTE ON DBMS_LOGMNR_D TO flinkuser; GRANT SELECT ON V_$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_$ARCHIVE_DEST_STATUS TO flinkuser;
2.2 對于Oracle CDB數(shù)據(jù)庫,執(zhí)行如下sql
CREATE USER flinkuser IDENTIFIED BY flinkpw DEFAULT TABLESPACE logminer_tbs QUOTA UNLIMITED ON logminer_tbs CONTAINER=ALL; GRANT CREATE SESSION TO flinkuser CONTAINER=ALL; GRANT SET CONTAINER TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$DATABASE to flinkuser CONTAINER=ALL; GRANT FLASHBACK ANY TABLE TO flinkuser CONTAINER=ALL; GRANT SELECT ANY TABLE TO flinkuser CONTAINER=ALL; GRANT SELECT_CATALOG_ROLE TO flinkuser CONTAINER=ALL; GRANT EXECUTE_CATALOG_ROLE TO flinkuser CONTAINER=ALL; GRANT SELECT ANY TRANSACTION TO flinkuser CONTAINER=ALL; GRANT LOGMINING TO flinkuser CONTAINER=ALL; GRANT CREATE TABLE TO flinkuser CONTAINER=ALL; -- need not to execute if set scan.incremental.snapshot.enabled=true(default) GRANT LOCK ANY TABLE TO flinkuser CONTAINER=ALL; GRANT CREATE SEQUENCE TO flinkuser CONTAINER=ALL; GRANT EXECUTE ON DBMS_LOGMNR TO flinkuser CONTAINER=ALL; GRANT EXECUTE ON DBMS_LOGMNR_D TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$LOG TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$LOG_HISTORY TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$LOGMNR_LOGS TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$LOGMNR_CONTENTS TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$LOGMNR_PARAMETERS TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$LOGFILE TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$ARCHIVED_LOG TO flinkuser CONTAINER=ALL; GRANT SELECT ON V_$ARCHIVE_DEST_STATUS TO flinkuser CONTAINER=ALL;
三、指定oracle表、庫級啟用
-- 指定表啟用補(bǔ)充日志記錄: ALTER TABLE databasename.tablename ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS; -- 為數(shù)據(jù)庫的所有表啟用 ALTER DATABASE ADD SUPPLEMENTAL LOG DATA (ALL) COLUMNS; -- 指定數(shù)據(jù)庫啟用補(bǔ)充日志記錄 ALTER DATABASE ADD SUPPLEMENTAL LOG DATA;
四、使用flink-connector-oracle-cdc實(shí)現(xiàn)數(shù)據(jù)庫同步
4.1 引入pom依賴
<dependency>
<groupId>com.ververica</groupId>
<artifactId>flink-connector-oracle-cdc</artifactId>
<version>2.4.0</version>
</dependency>4.2 Java主代碼
package test.datastream.cdc.oracle;
import com.ververica.cdc.connectors.oracle.OracleSource;
import com.ververica.cdc.debezium.JsonDebeziumDeserializationSchema;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.SourceFunction;
import org.apache.flink.streaming.api.windowing.assigners.TumblingProcessingTimeWindows;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.types.Row;
import test.datastream.cdc.oracle.function.CacheDataAllWindowFunction;
import test.datastream.cdc.oracle.function.CdcString2RowMap;
import test.datastream.cdc.oracle.function.DbCdcSinkFunction;
import java.util.Properties;
public class OracleCdcExample {
public static void main(String[] args) throws Exception {
Properties properties = new Properties();
//數(shù)字類型數(shù)據(jù) 轉(zhuǎn)換為字符
properties.setProperty("decimal.handling.mode", "string");
SourceFunction<String> sourceFunction = OracleSource.<String>builder()
// .startupOptions(StartupOptions.latest()) // 從最晚位點(diǎn)啟動(dòng)
.url("jdbc:oracle:thin:@localhost:1521:orcl")
.port(1521)
.database("ORCL") // monitor XE database
.schemaList("c##flink_user") // monitor inventory schema
.tableList("c##flink_user.TEST2") // monitor products table
.username("c##flink_user")
.password("flinkpw")
.debeziumProperties(properties)
.deserializer(new JsonDebeziumDeserializationSchema()) // converts SourceRecord to JSON String
.build();
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
DataStreamSource<String> source = env.addSource(sourceFunction).setParallelism(1);// use parallelism 1 for sink to keep message ordering
SingleOutputStreamOperator<Row> mapStream = source.flatMap(new CdcString2RowMap());
SingleOutputStreamOperator<Row[]> winStream = mapStream.windowAll(TumblingProcessingTimeWindows.of(Time.seconds(5)))
.process(new CacheDataAllWindowFunction());
//批量同步
winStream.addSink(new DbCdcSinkFunction(null));
env.execute();
}
}4.3json轉(zhuǎn)換為row
package test.datastream.cdc.oracle.function;
import cn.com.victorysoft.common.configuration.VsConfiguration;
import org.apache.flink.api.common.functions.RichFlatMapFunction;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.types.Row;
import org.apache.flink.types.RowKind;
import org.apache.flink.util.Collector;
import test.datastream.cdc.CdcConstants;
import java.sql.Timestamp;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;
/**
* @desc cdc json解析,并轉(zhuǎn)換為Row
*/
public class CdcString2RowMap extends RichFlatMapFunction<String, Row> {
private Map<String,Integer> columnMap =new HashMap<>();
@Override
public void open(Configuration parameters) throws Exception {
columnMap.put("ID",0);
columnMap.put("NAME",1);
columnMap.put("DESCRIPTION",2);
columnMap.put("AGE",3);
columnMap.put("CREATE_TIME",4);
columnMap.put("SCORE",5);
columnMap.put("C_1",6);
columnMap.put("B_1",7);
}
@Override
public void flatMap(String s, Collector<Row> collector) throws Exception {
System.out.println("receive: "+s);
VsConfiguration conf=VsConfiguration.from(s);
String op = conf.getString(CdcConstants.K_OP);
VsConfiguration before = conf.getConfiguration(CdcConstants.K_BEFORE);
VsConfiguration after = conf.getConfiguration(CdcConstants.K_AFTER);
Row row =null;
if(CdcConstants.OP_C.equals(op)){
//插入,使用after數(shù)據(jù)
row = convertToRow(after);
row.setKind(RowKind.INSERT);
}else if(CdcConstants.OP_U.equals(op)){
//更新,使用after數(shù)據(jù)
row = convertToRow(after);
row.setKind(RowKind.UPDATE_AFTER);
}else if(CdcConstants.OP_D.equals(op)){
//刪除,使用before數(shù)據(jù)
row = convertToRow(before);
row.setKind(RowKind.DELETE);
}else {
//r 操作,使用after數(shù)據(jù)
row = convertToRow(after);
row.setKind(RowKind.INSERT);
}
collector.collect(row);
}
private Row convertToRow(VsConfiguration data){
Set<String> keys = data.getKeys();
int size = keys.size();
Row row=new Row(8);
int i=0;
for (String key:keys) {
Integer index = this.columnMap.get(key);
Object value=data.get(key);
if(key.equals("CREATE_TIME")){
//long日期轉(zhuǎn)timestamp
value=long2Timestamp((Long)value);
}
row.setField(index,value);
}
return row;
}
private static java.sql.Timestamp long2Timestamp(Long time){
Timestamp timestamp = new Timestamp(time/1000);
System.out.println(timestamp);
return timestamp;
}
}到此這篇關(guān)于使用Flink CDC實(shí)現(xiàn) Oracle數(shù)據(jù)庫數(shù)據(jù)同步的文章就介紹到這了,更多相關(guān)Flink CDC Oracle數(shù)據(jù)同步內(nèi)容請搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家!
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