Hi Ayan,
Depends on the version of Spark you are using.
Have you tried updating stats in Hive?
ANALYZE TABLE ${DATABASE}.${TABLE} PARTITION (${PARTITION_NAME}) COMPUTE
STATISTICS FOR COLUMNS
and then do
show create table ${TABLE}
HTH
Dr Mich Talebzadeh
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On 7 October 2016 at 03:46, ayan guha <guha.a...@gmail.com> wrote:
> Posting with correct subject.....
>
> On Fri, Oct 7, 2016 at 12:37 PM, ayan guha <guha.a...@gmail.com> wrote:
>
>> Hi
>>
>> Faced one issue:
>>
>> - Writing Hive Partitioned table using
>>
>> df.withColumn("partition_date",to_date(df["INTERVAL_DATE"]))
>> .write.partitionBy('partition_date').saveAsTable("sometable"
>> ,mode="overwrite")
>>
>> - Data got written to HDFS fine. I can see the folders with partition
>> names such as
>>
>> /app/somedb/hive/somedb.db/sometable/partition_date=2016-09-28
>> /app/somedb/hive/somedb.db/sometable/partition_date=2016-09-29
>>
>> and so on.
>> - Also, _common_metadata & _metadata files are written properly
>>
>> - I can read data from spark fine using
>> read.parquet("/app/somedb/hive/somedb.db/sometable").
>> Printschema showing all columns.
>>
>> - However, I can not read from hive.
>>
>> Problem 1: Hive does not think the table is partitioned
>> Problem 2: Hive sees only 1 column
>> array<string> from deserializer
>> Problem 3: MSCK repair table failed, saying partitions are not in
>> Metadata.
>>
>> Question: Is it a known issue with Spark to write to Hive partitioned
>> table?
>>
>>
>> --
>> Best Regards,
>> Ayan Guha
>>
>
>
>
> --
> Best Regards,
> Ayan Guha
>
