Flink on zeppelin 初试2

先跟鸡哥打个广告 ，博客地址: https://me.csdn.net/weixin_47482194

写的博客很有水平的，上了几次官网推荐了。

 

1，首先配置好与hive的集成

2，该导入到flink的包都导入到flink lib下面，我是CDH版本，基本包如下：

对于这个地方不懂的同学可以评论留言，这是踩过坑的。。

 

3，实践操作：

我们正常些代码去查询hive，代码如下：

public class SourceData2hive_ods {


    private static final String KAFKA_SQL = "CREATE TABLE kafkaTable (" +
            " category_id STRING," +
            " user_id STRING ," +
            " item_id STRING ," +
            " behavior STRING ," +
            " ts STRING ," +
            " t_s AS TO_TIMESTAMP(FROM_UNIXTIME(cast(ts AS BIGINT), 'yyyy-MM-dd HH:mm:ss'))," +
//            " t_s AS TO_TIMESTAMP(FROM_UNIXTIME(cast(ts AS BIGINT), 'yyyy-MM-dd HH:mm:ss'))" +
            " WATERMARK FOR t_s AS t_s - INTERVAL '5' SECOND " +
            ") WITH (" +
            " 'connector' = 'kafka'," +
            " 'topic' = 'ods_kafka'," +
            " 'properties.bootstrap.servers' = 'dev-ct6-dc-worker01:9092,dev-ct6-dc-worker02:9092,dev-ct6-dc-worker03:9092'," +
            " 'properties.group.id' = 'test1'," +
            " 'format' = 'json'," +
            " 'scan.startup.mode' = 'earliest-offset'" +
            ")";

    private static final String hiveSql = "CREATE  TABLE  ods_table (" +
            " category_id STRING," +
            " user_id STRING ," +
            " item_id STRING ," +
            " behavior STRING ," +
            " ts STRING " +
            ") partitioned by (dt string,hr string) " +
            "stored as PARQUET " +
            "TBLPROPERTIES (" +
            "  'partition.time-extractor.timestamp-pattern'='$dt $hr:00:00'," +
            "  'sink.partition-commit.delay'='5 s'," +
            "  'sink.partition-commit.trigger'='partition-time'," +
//            "  'sink.partition-commit.trigger'='process-time'," +
            "  'sink.partition-commit.policy.kind'='metastore,success-file'" +
            ")";

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

        StreamExecutionEnvironment bsEnv = StreamExecutionEnvironment.getExecutionEnvironment();
        EnvironmentSettings bsSettings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build();
        StreamTableEnvironment tEnv = StreamTableEnvironment.create(bsEnv, bsSettings);
        bsEnv.enableCheckpointing(5000);
        bsEnv.setStreamTimeCharacteristic(TimeCharacteristic.EventTime);
//        bsEnv.setStreamTimeCharacteristic(TimeCharacteristic.ProcessingTime);

        String name = "myhive";
        String defaultDatabase = "flink";
//        String hiveConfDir = "/wyyt/software/flink-1.11.0";
//        String hiveConfDir = "/wyyt/software/flink-1.11.0/conf/";
        String hiveConfDir = "G:/Flink SQL开发文件";
        String version = "1.1.0";

        HiveCatalog hive = new HiveCatalog(name, defaultDatabase, hiveConfDir, version);

        tEnv.registerCatalog("myhive", hive);
        tEnv.useCatalog("myhive");

        tEnv.getConfig().setSqlDialect(SqlDialect.DEFAULT);
        tEnv.executeSql("drop table if exists kafkaTable");
        tEnv.executeSql(KAFKA_SQL);
//        tEnv.executeSql("select * from  kafkaTable").print();

        tEnv.getConfig().setSqlDialect(SqlDialect.HIVE);
        tEnv.executeSql("drop table if exists  ods_table");
//
//      如果hive中已经存在了相应的表，则这段代码省略

        tEnv.executeSql(hiveSql);
//
        String insertSql = "insert into ods_table SELECT category_id, user_id,item_id,behavior,ts, " +
                " DATE_FORMAT(t_s, 'yyyy-MM-dd'), DATE_FORMAT(t_s, 'HH') FROM kafkaTable";
        tEnv.executeSql(insertSql);
    }
}

 

 

我们在zeppelin写查询，就很简单了：

通过 %flink  指定这是代码模式。。。简单吧。。。。诶。

 

 创建表：

 

对于API跟不懂的关键字说明：

github上的资料：https://github.com/apache/zeppelin/blob/master/docs/interpreter/flink.md#paragraph-local-properties

 

 

 

 

 

 

未完待续。。。。。。