11.8 spark SQL读取hive数据

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1，启动hdfs集群

2，启动hive

create database testdb 创建testdb库

关闭hive保留关键字检查功能：

set hive.support.sql11.reserved.keywords=false

创建一张userlog表：

CREATE TABLE IF NOT EXISTS testdb.userlog(

date string ,

timestamp string ,

user_id string ,

page_id string ,

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channel string ,

action string

)

ROW FORMAT DELIMITED FIELDS TERMINATED BY '\t' ;

表中插入数据：加载本地数据到hive

load data local inpath '/root/resource/userLog' into table testdb.userlog;

hive中的测试操作：是用来和Spark core性能对比

查询page的PV

SELECT date,page_id,count(*) pv FROM userlog WHERE action = 'View' GROUP BY date, page_id ORDER BY pv DESC LIMIT 10;

查询page的UV

SELECT date, page_id, count(distinct(user_id)) uv FROM userlog WHERE action = 'View' GROUP BY date,page_id ORDER BY uv DESC LIMIT 3;

最热门的channel

SELECT date,channel,count(*) channelpv FROM userlog WHERE action = 'View' GROUP BY date, channel ORDER BY channelpv DESC LIMIT 10;

spark core操作：

1，启动spark

2，开启Hive的metaStore服务 在~目录下 ./startHiveMetastoreService.sh启动

3，启动spark core ： ./spark-shell --master spark://node1:7077 --total-executor-cores 3

4、import org.apache.spark.sql.hive.HiveContext

val hc = new HiveContext(sc)

hc.sql("show databases").show //查看数据库结构

hc.sql("use testdb").show //切换到testdb库

hc.sql("SELECT date,page_id,count(*) pv FROM userlog WHERE action = 'View' GROUP BY date, page_id ORDER BY pv DESC LIMIT 10").show