I am looking at ORC. I insert the data using the following query.
sqlContext.sql(" CREATE EXTERNAL TABLE IF NOT EXISTS records (id STRING,
record STRING) PARTITIONED BY (datePartition STRING, idPartition STRING)
stored as ORC LOCATION '/user/users' ")
sqlContext.sql(" orc.compress= SNAPPY")
sqlContext.sql(
""" from recordsTemp ps insert overwrite table users
partition(datePartition , idPartition ) select ps.id, ps.record ,
ps.datePartition, ps.idPartition """.stripMargin)
On Sun, May 22, 2016 at 12:37 AM, Mich Talebzadeh <mich.talebza...@gmail.com
> wrote:
> where is your base table and what format is it Parquet, ORC etc)
>
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> Dr Mich Talebzadeh
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> On 22 May 2016 at 08:34, SRK <swethakasire...@gmail.com> wrote:
>
>> Hi,
>>
>> In my Spark SQL query to insert data, I have around 14,000 partitions of
>> data which seems to be causing memory issues. How can I insert the data
>> for
>> 100 partitions at a time to avoid any memory issues?
>>
>>
>>
>> --
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