hive create table as select stored as parquet

Parquet columnar storage format in Hive 0.13.0 and later. CREATE TABLE AS SELECT: ... To make the new table also use Parquet format, include the clause STORED AS PARQUET in the CREATE TABLE LIKE PARQUET statement. table ("src") df. Example. sqlContext.sql("CREATE EXTERNAL TABLE nedw_11 (code string,name string,quantity int, price float) PARTITIONED BY (`productID` int) STORED AS parquet LOCATION "/user/edureka_431591/ 'custResult.parquet'") If ... because it currently does not support the STORED BY clause needed for HBase tables. Set dfs.block.size to 256 MB in hdfs-site.xml. mode (SaveMode. create table transaction(no int,tdate string,userno int,amt int,pro string,city string,pay … CREATE TABLE parquet_table_name (x INT, y STRING) STORED AS PARQUET; Note: Once you create a Parquet table, you can query it or insert into it through other components such as Impala and Spark. This page shows how to create Hive tables with storage file format as Parquet, Orc and Avro via Hive SQL (HQL). The following examples show you how to create managed tables and similar syntax can be applied to create external tables if Parquet, Orc or Avro format already exist in HDFS. I would create a new external table for your data set by selecting all the data from the source partitions you are after. var query = "CREATE TABLE Test(EMP_ID string,Organisation string,Org_Skill string,EMP_Name string)ROW FORMAT SERDE 'parquet.hive.serde.ParquetHiveSerDe' STORED AS INPUTFORMAT 'parquet.hive.DeprecatedParquetInputFormat' OUTPUTFORMAT 'parquet.hive.DeprecatedParquetOutputFormat' TBLPROPERTIES ('PARQUET.COMPRESS'='SNAPPY')" Parquet is built from the ground up with complex nested data structures in mind, and uses the record shredding and assembly algorithm described in the Dremel paper. To convert data into Parquet format, you can use CREATE TABLE AS SELECT (CTAS) queries. Athena uses this class when it needs to deserialize data stored in Parquet: For more information, see , and . Create such tables in Hive, then query them through Impala. ParquetHiveSerDe is used for data stored in Parquet Format . Then you would have a table and file that can be utilized. Creating a Parquet Hive table, instead of the default Hive table, allows for compression of the table to save space and minimize the size of the table to help speed up processing. hive documentation: PARQUET. To enhance performance on Parquet tables in Hive, see Enabling Query Vectorization. You can't do a create table as select statement as of now with external tables, so you would need to create the table … // Create a Hive managed Parquet table, with HQL syntax instead of the Spark SQL native syntax // `USING hive` sql ("CREATE TABLE hive_records(key int, value string) STORED AS PARQUET") // Save DataFrame to the Hive managed table val df = spark. Storing a hive table as a parquet file with a snappy compression in a traditional hive shell Create a hive table called transaction and load it with records using the load command. Create Table As Select (CTAS) ... Before Hive 0.8.0, CREATE TABLE LIKE view_name would make a copy of the view. write. hive> CREATE TABLE inv_hive_parquet( trans_id int, product varchar(50), trans_dt date ) PARTITIONED BY ( year int) STORED AS PARQUET TBLPROPERTIES ('PARQUET.COMPRESS'='SNAPPY'); Note that if the table is created in Big SQL and then populated in Hive, then this table property can also be used to enable SNAPPY compression.

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