简介

        Spark SQL  provides JDBC connectivity, which is useful for connecting business intelligence (BI) tools to a Spark cluster and for sharing a cluster across multipleusers. The JDBC server runs as a standalone Spark driver program that can be shared by multiple clients. Any client can cache tables in memory, query them, and so on and the cluster resources and cached data will be shared among all of them.

    Spark SQL’s JDBC server corresponds to the HiveServer2 in Hive.  It is also known as the “Thrift server” since it uses the Thrift communication protocol. Note that the JDBC server requires Spark be built with Hive support

运行环境

集群环境：CDH5.3.0

具体JAR版本如下：

spark版本：1.2.0-cdh5.3.0

hive版本：0.13.1-cdh5.3.0

hadoop版本：2.5.0-cdh5.3.0

启动 JDBC server

cd /etc/spark/confln -s /etc/hive/conf/hive-site.xml hive-site.xmlcd /opt/cloudera/parcels/CDH/lib/spark/chmod- -R 777 logs/cd /opt/cloudera/parcels/CDH/lib/spark/sbin./start-thriftserver.sh  --master yarn --hiveconf hive.server2.thrift.port=10008

 Connecting to the JDBC server with Beeline

cd /opt/cloudera/parcels/CDH/lib/spark/binbeeline -u jdbc:hive2://hadoop04:10000[root@hadoop04 bin]# beeline -u jdbc:hive2://hadoop04:10000scan complete in 2msConnecting to jdbc:hive2://hadoop04:10000Connected to: Spark SQL (version 1.2.0)Driver: Hive JDBC (version 0.13.1-cdh5.3.0)Transaction isolation: TRANSACTION_REPEATABLE_READBeeline version 0.13.1-cdh5.3.0 by Apache Hive0: jdbc:hive2://hadoop04:10000>

Working with Beeline

Within the Beeline client, you can use standard HiveQL commands to create, list, and query tables. You can find the full details of HiveQL in the  Hive Language Manual,but here, we show a few common operations.

CREATE TABLE IF NOT EXISTS mytable (key INT, value STRING)ROW FORMAT DELIMITED FIELDS TERMINATED BY ',';create table mytable(name string,addr string,status string) row format delimited fields terminated by '#'#加载本地文件load data local inpath '/external/tmp/data.txt' into table mytable#加载hdfs文件load data inpath 'hdfs://ju51nn/external/tmp/data.txt' into table mytable;describe mytable;explain select * from mytable where name = '张三'select * from mytable where name = '张三'   cache table mytable select count(*) total,count(distinct addr) num1,count(distinct status) num2 from mytable where addr='gz';  uncache table mytable

使用数据示例

张三#广州#学生李四#贵州#教师王五#武汉#讲师赵六#成都#学生lisa#广州#学生lily#gz#studene

Standalone Spark SQL Shell

Spark SQL also supports a simple shell you can use as a single process: spark-sql

它主要用于本地的开发环境，在共享集群环境中，请使用JDBC SERVER

cd /opt/cloudera/parcels/CDH/lib/spark/bin./spark-sql