HIVE存储格式ORC、PARQUET对比

　　hive有三种默认的存储格式，TEXT、ORC、PARQUET。TEXT是默认的格式，ORC、PARQUET是列存储格式，占用空间和查询效率是不同的，专门测试过后记录一下。

一：建表语句差别

create table if not exists text(
a bigint
) partitioned by (dt string)
row format delimited fields terminated by '\001'
location '/hdfs/text/';

create table if not exists orc(
a bigint)
partitioned by (dt string)
row format delimited fields terminated by '\001'
stored as orc
location '/hdfs/orc/';

create table if not exists parquet(
a bigint)
partitioned by (dt string)
row format delimited fields terminated by '\001'
stored as parquet
location '/hdfs/parquet/';

其实就是stored as 后面跟的不一样

二：HDFS存储对比

parquet	orc	text
709M	275M	1G
687M	249M	1G
647M	265M	1G

三：查询时间对比

parquet	orc	text
36.451	26.133	42.574
38.425	29.353	41.673
36.647	27.825	43.938

四：文件如何生成

val sparkSession = SparkSession.builder().master("local").appName("pushFunnelV3").getOrCreate()
val javasc = new JavaSparkContext(sparkSession.sparkContext)
val nameRDD = javasc.parallelize(util.Arrays.asList("{'name':'zhangsan','age':'18'}", "{'name':'lisi','age':'19'}")).rdd;
sparkSession.read.json(nameRDD).write.mode(SaveMode.Overwrite).csv("/data/aa")
sparkSession.read.json(nameRDD).write.mode(SaveMode.Overwrite).orc("/data/bb")
sparkSession.read.json(nameRDD).write.mode(SaveMode.Overwrite).parquet("/data/cc")