24、Flink 的table api与sql之Catalogs（java api操作数据库、表）-2

Flink 系列文章

1、Flink 部署、概念介绍、source、transformation、sink使用示例、四大基石介绍和示例等系列综合文章链接

13、Flink 的table api与sql的基本概念、通用api介绍及入门示例
14、Flink 的table api与sql之数据类型: 内置数据类型以及它们的属性
15、Flink 的table api与sql之流式概念-详解的介绍了动态表、时间属性配置（如何处理更新结果）、时态表、流上的join、流上的确定性以及查询配置
16、Flink 的table api与sql之连接外部系统: 读写外部系统的连接器和格式以及FileSystem示例（1）
16、Flink 的table api与sql之连接外部系统: 读写外部系统的连接器和格式以及Elasticsearch示例（2）
16、Flink 的table api与sql之连接外部系统: 读写外部系统的连接器和格式以及Apache Kafka示例（3）
16、Flink 的table api与sql之连接外部系统: 读写外部系统的连接器和格式以及JDBC示例（4）

16、Flink 的table api与sql之连接外部系统: 读写外部系统的连接器和格式以及Apache Hive示例（6）

20、Flink SQL之SQL Client: 不用编写代码就可以尝试 Flink SQL，可以直接提交 SQL 任务到集群上

22、Flink 的table api与sql之创建表的DDL
24、Flink 的table api与sql之Catalogs（介绍、类型、java api和sql实现ddl、java api和sql操作catalog）-1
24、Flink 的table api与sql之Catalogs（java api操作数据库、表）-2

26、Flink 的SQL之概览与入门示例
27、Flink 的SQL之SELECT (select、where、distinct、order by、limit、集合操作和去重)介绍及详细示例（1）
27、Flink 的SQL之SELECT (SQL Hints 和 Joins)介绍及详细示例（2）
27、Flink 的SQL之SELECT (窗口函数)介绍及详细示例（3）
27、Flink 的SQL之SELECT (窗口聚合)介绍及详细示例（4）
27、Flink 的SQL之SELECT (Group Aggregation分组聚合、Over Aggregation Over聚合和 Window Join 窗口关联)介绍及详细示例（5）
27、Flink 的SQL之SELECT (Top-N、Window Top-N 窗口 Top-N 和 Window Deduplication 窗口去重)介绍及详细示例（6）
27、Flink 的SQL之SELECT (Pattern Recognition 模式检测)介绍及详细示例（7）

29、Flink SQL之DESCRIBE、EXPLAIN、USE、SHOW、LOAD、UNLOAD、SET、RESET、JAR、JOB Statements、UPDATE、DELETE（1）
29、Flink SQL之DESCRIBE、EXPLAIN、USE、SHOW、LOAD、UNLOAD、SET、RESET、JAR、JOB Statements、UPDATE、DELETE（2）
30、Flink SQL之SQL 客户端（通过kafka和filesystem的例子介绍了配置文件使用-表、视图等）
32、Flink table api和SQL 之用户自定义 Sources & Sinks实现及详细示例
41、Flink之Hive 方言介绍及详细示例
42、Flink 的table api与sql之Hive Catalog
43、Flink之Hive 读写及详细验证示例
44、Flink之module模块介绍及使用示例和Flink SQL使用hive内置函数及自定义函数详细示例–网上有些说法好像是错误的

文章目录

本文简单介绍了通过java api操作数据库、表，分别提供了具体可运行的例子。
本文依赖flink和hive、hadoop集群能正常使用。
本文分为2个部分，即数据库操作、表操作。
本文示例java api的实现是通过Flink 1.13.5版本做的示例，SQL 如果没有特别说明则是Flink 1.17版本。

五、Catalog API

1、数据库操作

下文列出了一般的数据库操作，示例是以jdbccatalog为示例，flink的版本是1.17.0。

// create database
catalog.createDatabase("mydb",newCatalogDatabaseImpl(...),false);// drop database
catalog.dropDatabase("mydb",false);// alter database
catalog.alterDatabase("mydb",newCatalogDatabaseImpl(...),false);// get databse
catalog.getDatabase("mydb");// check if a database exist
catalog.databaseExists("mydb");// list databases in a catalog
catalog.listDatabases("mycatalog");

1）、jdbccatalog示例

pom.xml

<properties><encoding>UTF-8</encoding><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><maven.compiler.source>1.8</maven.compiler.source><maven.compiler.target>1.8</maven.compiler.target><java.version>1.8</java.version><scala.version>2.12</scala.version><flink.version>1.17.0</flink.version></properties><dependencies><dependency><groupId>jdk.tools</groupId><artifactId>jdk.tools</artifactId><version>1.8</version><scope>system</scope><systemPath>${JAVA_HOME}/lib/tools.jar</systemPath></dependency><!-- https://mvnrepository.com/artifact/org.apache.flink/flink-clients --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-clients</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-scala_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-java</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-scala_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-java</artifactId><version>${flink.version}</version><scope>provided</scope></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-api-scala-bridge_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-api-java-bridge</artifactId><version>${flink.version}</version><scope>provided</scope></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-planner_2.12</artifactId><version>${flink.version}</version><scope>test</scope></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-common</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-jdbc</artifactId><version>3.1.0-1.17</version><scope>provided</scope></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-csv</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-json</artifactId><version>${flink.version}</version></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>5.1.38</version></dependency><!-- https://mvnrepository.com/artifact/org.apache.flink/flink-table-planner --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-planner_2.12</artifactId><version>${flink.version}</version><scope>test</scope></dependency><!-- https://mvnrepository.com/artifact/org.apache.flink/flink-table-planner-loader --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-planner-loader</artifactId><version>${flink.version}</version><scope>provided</scope></dependency><!-- https://mvnrepository.com/artifact/org.apache.flink/flink-table-runtime --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-runtime</artifactId><version>${flink.version}</version><scope>provided</scope></dependency></dependencies>

java

importjava.util.List;importorg.apache.flink.connector.jdbc.catalog.JdbcCatalog;importorg.apache.flink.streaming.api.environment.StreamExecutionEnvironment;importorg.apache.flink.table.api.bridge.java.StreamTableEnvironment;importorg.apache.flink.table.catalog.Catalog;importorg.apache.flink.table.catalog.exceptions.CatalogException;importorg.apache.flink.table.catalog.exceptions.DatabaseNotExistException;/**
 * @author alanchan
 *
 */publicclassTestJdbcCatalogDemo{/**
     * @param args
     * @throws DatabaseNotExistException
     * @throws CatalogException
     */publicstaticvoidmain(String[] args)throwsCatalogException,DatabaseNotExistException{// envStreamExecutionEnvironment env =StreamExecutionEnvironment.getExecutionEnvironment();StreamTableEnvironment tenv =StreamTableEnvironment.create(env);// public JdbcCatalog(// String catalogName,// String defaultDatabase,// String username,// String pwd,// String baseUrl)// CREATE CATALOG alan_catalog WITH(// 'type' = 'jdbc',// 'default-database' = 'test?useSSL=false',// 'username' = 'root',// 'password' = 'root',// 'base-url' = 'jdbc:mysql://192.168.10.44:3306'// );Catalog catalog =newJdbcCatalog("alan_catalog","test?useSSL=false","root","123456","jdbc:mysql://192.168.10.44:3306");// Register the catalog
        tenv.registerCatalog("alan_catalog", catalog);List<String> tables = catalog.listTables("test");//        System.out.println("test tables:" + tablesfor(String table : tables){System.out.println("Database：test  tables："+table);}}}

运行结果

Database：test  tables：allowinsert
Database：test  tables：author
Database：test  tables：batch_job_execution
Database：test  tables：batch_job_execution_context
Database：test  tables：batch_job_execution_params
Database：test  tables：batch_job_execution_seq
Database：test  tables：batch_job_instance
Database：test  tables：batch_job_seq
Database：test  tables：batch_step_execution
Database：test  tables：batch_step_execution_context
Database：test  tables：batch_step_execution_seq
Database：test  tables：book
Database：test  tables：customertest
Database：test  tables：datax_user
Database：test  tables：dm_sales
Database：test  tables：dms_attach_t
Database：test  tables：dx_user
Database：test  tables：dx_user_copy
Database：test  tables：employee
Database：test  tables：hibernate_sequence
Database：test  tables：permissions
Database：test  tables：person
Database：test  tables：personinfo
Database：test  tables：role
Database：test  tables：studenttotalscore
Database：test  tables：t_consume
Database：test  tables：t_czmx_n
Database：test  tables：t_kafka_flink_user
Database：test  tables：t_merchants
Database：test  tables：t_recharge
Database：test  tables：t_user
Database：test  tables：t_withdrawal
Database：test  tables：updateonly
Database：test  tables：user

2）、hivecatalog示例-查询指定数据库下的表名称

本示例需要在有hadoop和hive环境执行，本示例是打包执行jar文件。
关于flink与hive的集成请参考：42、Flink 的table api与sql之Hive Catalog

pom.xml

<properties><encoding>UTF-8</encoding><project.build.sourceEncoding>UTF-8</project.build.sourceEncoding><maven.compiler.source>1.8</maven.compiler.source><maven.compiler.target>1.8</maven.compiler.target><java.version>1.8</java.version><scala.version>2.12</scala.version><flink.version>1.13.6</flink.version></properties><dependencies><dependency><groupId>jdk.tools</groupId><artifactId>jdk.tools</artifactId><version>1.8</version><scope>system</scope><systemPath>${JAVA_HOME}/lib/tools.jar</systemPath></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-clients_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-scala_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-java</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-scala_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-streaming-java_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-api-scala-bridge_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-api-java-bridge_2.12</artifactId><version>${flink.version}</version></dependency><!-- flink执行计划,这是1.9版本之前的 --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-planner_2.12</artifactId><version>${flink.version}</version></dependency><!-- blink执行计划,1.11+默认的 --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-planner-blink_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-table-common</artifactId><version>${flink.version}</version></dependency><!-- flink连接器 --><dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-kafka_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-sql-connector-kafka_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-jdbc_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-csv</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-json</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-connector-hive_2.12</artifactId><version>${flink.version}</version></dependency><dependency><groupId>org.apache.hive</groupId><artifactId>hive-metastore</artifactId><version>2.1.0</version></dependency><dependency><groupId>org.apache.hive</groupId><artifactId>hive-exec</artifactId><version>3.1.2</version></dependency><dependency><groupId>org.apache.flink</groupId><artifactId>flink-shaded-hadoop-2-uber</artifactId><version>2.7.5-10.0</version></dependency><dependency><groupId>mysql</groupId><artifactId>mysql-connector-java</artifactId><version>5.1.38</version><!--<version>8.0.20</version> --></dependency><!-- 高性能异步组件：Vertx --><dependency><groupId>io.vertx</groupId><artifactId>vertx-core</artifactId><version>3.9.0</version></dependency><dependency><groupId>io.vertx</groupId><artifactId>vertx-jdbc-client</artifactId><version>3.9.0</version></dependency><dependency><groupId>io.vertx</groupId><artifactId>vertx-redis-client</artifactId><version>3.9.0</version></dependency><!-- 日志 --><dependency><groupId>org.slf4j</groupId><artifactId>slf4j-log4j12</artifactId><version>1.7.7</version><scope>runtime</scope></dependency><dependency><groupId>log4j</groupId><artifactId>log4j</artifactId><version>1.2.17</version><scope>runtime</scope></dependency><dependency><groupId>com.alibaba</groupId><artifactId>fastjson</artifactId><version>1.2.44</version></dependency><dependency><groupId>org.projectlombok</groupId><artifactId>lombok</artifactId><version>1.18.2</version><scope>provided</scope></dependency></dependencies><build><sourceDirectory>src/main/java</sourceDirectory><plugins><!-- 编译插件 --><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-compiler-plugin</artifactId><version>3.5.1</version><configuration><source>1.8</source><target>1.8</target><!--<encoding>${project.build.sourceEncoding}</encoding> --></configuration></plugin><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-surefire-plugin</artifactId><version>2.18.1</version><configuration><useFile>false</useFile><disableXmlReport>true</disableXmlReport><includes><include>**/*Test.*</include><include>**/*Suite.*</include></includes></configuration></plugin><!-- 打包插件(会包含所有依赖) --><plugin><groupId>org.apache.maven.plugins</groupId><artifactId>maven-shade-plugin</artifactId><version>2.3</version><executions><execution><phase>package</phase><goals><goal>shade</goal></goals><configuration><filters><filter><artifact>*:*</artifact><excludes><!-- zip -d learn_spark.jar META-INF/*.RSA META-INF/*.DSA META-INF/*.SF --><exclude>META-INF/*.SF</exclude><exclude>META-INF/*.DSA</exclude><exclude>META-INF/*.RSA</exclude></excludes></filter></filters><transformers><transformerimplementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer"><!-- 设置jar包的入口类(可选) --><mainClass> org.table_sql.TestHiveCatalogDemo</mainClass></transformer></transformers></configuration></execution></executions></plugin></plugins></build>

java

importjava.util.List;importorg.apache.flink.streaming.api.environment.StreamExecutionEnvironment;importorg.apache.flink.table.api.bridge.java.StreamTableEnvironment;importorg.apache.flink.table.catalog.exceptions.CatalogException;importorg.apache.flink.table.catalog.exceptions.DatabaseNotExistException;importorg.apache.flink.table.catalog.hive.HiveCatalog;/**
 * @author alanchan
 *
 */publicclassTestHiveCatalogDemo{/**
     * @param args
     * @throws DatabaseNotExistException 
     * @throws CatalogException 
     */publicstaticvoidmain(String[] args)throwsCatalogException,DatabaseNotExistException{StreamExecutionEnvironment env =StreamExecutionEnvironment.getExecutionEnvironment();StreamTableEnvironment tenv =StreamTableEnvironment.create(env);String name ="alan_hive";// testhive 数据库名称String defaultDatabase ="testhive";String hiveConfDir ="/usr/local/bigdata/apache-hive-3.1.2-bin/conf";HiveCatalog hiveCatalog =newHiveCatalog(name, defaultDatabase, hiveConfDir);
        tenv.registerCatalog("alan_hive", hiveCatalog);// 使用注册的catalog
        tenv.useCatalog("alan_hive");List<String> tables = hiveCatalog.listTables(defaultDatabase);// tables should contain "test"//        System.out.println("test tables:" + tablesfor(String table : tables){System.out.println("Database：testhive  tables："+ table);}}}

运行结果

################hive查询结果##################0: jdbc:hive2://server4:10000> use testhive;
No rows affected (0.021 seconds)0: jdbc:hive2://server4:10000> show tables;
+-----------------------+
|       tab_name        |
+-----------------------+
| apachelog             || col2row1              || col2row2              || cookie_info           || dual                  || dw_zipper             || emp                   || employee              || employee_address      || employee_connection   || ods_zipper_update     || row2col1              || row2col2              || singer                || singer2               || student               || student_dept          || student_from_insert   || student_hdfs          || student_hdfs_p        || student_info          || student_local         || student_partition     || t_all_hero_part_msck  || t_usa_covid19         || t_usa_covid19_p       || tab1                  || tb_dept01             || tb_dept_bucket        || tb_emp                || tb_emp01              || tb_emp_bucket         || tb_json_test1         || tb_json_test2         || tb_login              || tb_login_tmp          || tb_money              || tb_money_mtn          || tb_url                || the_nba_championship  || tmp_1                 || tmp_zipper            || user_dept             || user_dept_sex         ||users|| users_bucket_sort     || website_pv_info       || website_url_info      |
+-----------------------+
48 rows selected (0.027 seconds)################flink查询结果##################[alanchan@server2 bin]$ flink run  /usr/local/bigdata/flink-1.13.5/examples/table/table_sql-0.0.1-SNAPSHOT.jar
Database：testhive  tables：student
Database：testhive  tables：user_dept
Database：testhive  tables：user_dept_sex
Database：testhive  tables：t_all_hero_part_msck
Database：testhive  tables：student_local
Database：testhive  tables：student_hdfs
Database：testhive  tables：student_hdfs_p
Database：testhive  tables：tab1
Database：testhive  tables：student_from_insert
Database：testhive  tables：student_info
Database：testhive  tables：student_dept
Database：testhive  tables：student_partition
Database：testhive  tables：emp
Database：testhive  tables：t_usa_covid19
Database：testhive  tables：t_usa_covid19_p
Database：testhive  tables：employee
Database：testhive  tables：employee_address
Database：testhive  tables：employee_connection
Database：testhive  tables：dual
Database：testhive  tables：the_nba_championship
Database：testhive  tables：tmp_1
Database：testhive  tables：cookie_info
Database：testhive  tables：website_pv_info
Database：testhive  tables：website_url_info
Database：testhive  tables：users
Database：testhive  tables：users_bucket_sort
Database：testhive  tables：singer
Database：testhive  tables：apachelog
Database：testhive  tables：singer2
Database：testhive  tables：tb_url
Database：testhive  tables：row2col1
Database：testhive  tables：row2col2
Database：testhive  tables：col2row1
Database：testhive  tables：col2row2
Database：testhive  tables：tb_json_test1
Database：testhive  tables：tb_json_test2
Database：testhive  tables：tb_login
Database：testhive  tables：tb_login_tmp
Database：testhive  tables：tb_money
Database：testhive  tables：tb_money_mtn
Database：testhive  tables：tb_emp
Database：testhive  tables：dw_zipper
Database：testhive  tables：ods_zipper_update
Database：testhive  tables：tmp_zipper
Database：testhive  tables：tb_emp01
Database：testhive  tables：tb_emp_bucket
Database：testhive  tables：tb_dept01
Database：testhive  tables：tb_dept_bucket

3）、hivecatalog示例-创建database

本示例着重在于演示如何创建database，其如何构造函数来创建database。

pom.xml 参考示例2
java

importjava.util.HashMap;importjava.util.List;importjava.util.Map;importorg.apache.flink.streaming.api.environment.StreamExecutionEnvironment;importorg.apache.flink.table.api.bridge.java.StreamTableEnvironment;importorg.apache.flink.table.catalog.CatalogDatabase;importorg.apache.flink.table.catalog.CatalogDatabaseImpl;importorg.apache.flink.table.catalog.exceptions.CatalogException;importorg.apache.flink.table.catalog.exceptions.DatabaseAlreadyExistException;importorg.apache.flink.table.catalog.exceptions.DatabaseNotExistException;importorg.apache.flink.table.catalog.hive.HiveCatalog;/**
 * @author alanchan
 *
 */publicclassTestHiveCatalogDemo{/**
     * @param args
     * @throws DatabaseNotExistException
     * @throws CatalogException
     * @throws DatabaseAlreadyExistException
     */publicstaticvoidmain(String[] args)throwsCatalogException,DatabaseNotExistException,DatabaseAlreadyExistException{StreamExecutionEnvironment env =StreamExecutionEnvironment.getExecutionEnvironment();StreamTableEnvironment tenv =StreamTableEnvironment.create(env);String name ="alan_hive";// testhive 数据库名称String defaultDatabase ="testhive";String hiveConfDir ="/usr/local/bigdata/apache-hive-3.1.2-bin/conf";HiveCatalog hiveCatalog =newHiveCatalog(name, defaultDatabase, hiveConfDir);
        tenv.registerCatalog("alan_hive", hiveCatalog);// 使用注册的catalog
        tenv.useCatalog("alan_hive");List<String> tables = hiveCatalog.listTables(defaultDatabase);for(String table : tables){System.out.println("Database：testhive  tables："+ table);}//        public CatalogDatabaseImpl(Map<String, String> properties, @Nullable String comment) {//            this.properties = checkNotNull(properties, "properties cannot be null");//            this.comment = comment;//        }Map<String,String> properties =newHashMap();CatalogDatabase cd =newCatalogDatabaseImpl(properties,"this is new database,the name is alan_hivecatalog_hivedb");String newDatabaseName ="alan_hivecatalog_hivedb";
        hiveCatalog.createDatabase(newDatabaseName, cd,true);List<String> newTables = hiveCatalog.listTables(newDatabaseName);for(String table : newTables){System.out.println("Database：alan_hivecatalog_hivedb  tables："+ table);}}}

运行结果

##################  hive查询结果  #################################提交flink创建database前查询结果0: jdbc:hive2://server4:10000> show databases;
+----------------+
| database_name  |
+----------------+
| default        ||test|| testhive       |
+----------------+
3 rows selected (0.03 seconds)#####提交flink创建database后查询结果0: jdbc:hive2://server4:10000> show databases;
+--------------------------+
|      database_name       |
+--------------------------+
| alan_hivecatalog_hivedb  || default                  ||test|| testhive                 |
+--------------------------+
4 rows selected (0.023 seconds)##################  flink 查询结果  ################################ 由于只创建了database，其下是没有表的，故没有输出。至于testhive库下的表输出详见示例2，不再赘述。

2、表操作

表操作就是指hivecatalog的操作，因为jdbccatalog不能对库、表进行操作，当然查询类是可以的。故以下示例都是以hivecatalog进行说明。本处与24、Flink 的table api与sql之Catalogs（介绍、类型、java api和sql实现ddl、java api和sql操作catalog）-1的第三部分相似，具体参考其示例即可。不再赘述。

// create table
catalog.createTable(newObjectPath("mydb","mytable"),newCatalogTableImpl(...),false);// drop table
catalog.dropTable(newObjectPath("mydb","mytable"),false);// alter table
catalog.alterTable(newObjectPath("mydb","mytable"),newCatalogTableImpl(...),false);// rename table
catalog.renameTable(newObjectPath("mydb","mytable"),"my_new_table");// get table
catalog.getTable("mytable");// check if a table exist or not
catalog.tableExists("mytable");// list tables in a database
catalog.listTables("mydb");

本文简单介绍了通过java api操作数据库、表，分别提供了具体可运行的例子。

标签： flink sql flink 流批一体化

本文转载自: https://blog.csdn.net/chenwewi520feng/article/details/133862126
版权归原作者 一瓢一瓢的饮 alanchan 所有，如有侵权，请联系我们删除。

24、Flink 的table api与sql之Catalogs（java api操作数据库、表）-2

Flink 系列文章

文章目录

五、Catalog API

1、数据库操作

1）、jdbccatalog示例

2）、hivecatalog示例-查询指定数据库下的表名称

3）、hivecatalog示例-创建database

2、表操作

发表评论

“24、Flink 的table api与sql之Catalogs（java api操作数据库、表）-2”的评论:

关于作者

overfit同步小助手

相关阅读

文章导航