[jira] [Comment Edited] (SPARK-14172) Hive table partition predicate not passed down correctly
[
https://issues.apache.org/jira/browse/SPARK-14172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16189481#comment-16189481
]
Saktheesh Balaraj edited comment on SPARK-14172 at 10/4/17 9:21 AM:
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partitions. when joining 2 tables based on partition it's
going for full table scan in table A i.e using all 1000 partitions instead of
taking 2 partitions from Table A and join with Table B.
{noformat}
sqlContext.sql("select * from tableA a, tableB b where
a.trans_date=b.trans_date and a.trans_hour=b.trans_hour")
{noformat}
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1:
{noformat} select trans_date, a.trans_hour from table B {noformat}
step2:
{noformat} select * from tableA where trans_date= and
a.trans_hour = {noformat}
was (Author: saktheesh):
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
{noformat}
sqlContext.sql("select * from tableA a, tableB b where
a.trans_date=b.trans_date and a.trans_hour=b.trans_hour")
{noformat}
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1:
{noformat} select trans_date, a.trans_hour from table B {noformat}
step2:
{noformat} select * from tableA where trans_date= and
a.trans_hour = {noformat}
> Hive table partition predicate not passed down correctly
>
>
> Key: SPARK-14172
> URL: https://issues.apache.org/jira/browse/SPARK-14172
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Yingji Zhang
>Priority: Critical
>
> When the hive sql contains nondeterministic fields, spark plan will not push
> down the partition predicate to the HiveTableScan. For example:
> {code}
> -- consider following query which uses a random function to sample rows
> SELECT *
> FROM table_a
> WHERE partition_col = 'some_value'
> AND rand() < 0.01;
> {code}
> The spark plan will not push down the partition predicate to HiveTableScan
> which ends up scanning all partitions data from the table.
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[jira] [Comment Edited] (SPARK-14172) Hive table partition predicate not passed down correctly
[
https://issues.apache.org/jira/browse/SPARK-14172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16189481#comment-16189481
]
Saktheesh Balaraj edited comment on SPARK-14172 at 10/3/17 3:21 PM:
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
{noformat}
sqlContext.sql("select * from tableA a, tableB b where
a.trans_date=b.trans_date and a.trans_hour=b.trans_hour")
{noformat}
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1:
{noformat} select trans_date, a.trans_hour from table B {noformat}
step2:
{noformat} select * from tableA where trans_date= and
a.trans_hour = {noformat}
was (Author: saktheesh):
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
{noformat}
sqlContext.sql("select * from tableA a, tableB b where
a.trans_date=b.trans_date and a.trans_hour=b.trans_hour")
{noformat}
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1:
{noformat} select trans_date and a.trans_hour from table B {noformat}
step2:
{noformat} select * from tableA where trans_date= and
a.trans_hour = {noformat}
> Hive table partition predicate not passed down correctly
>
>
> Key: SPARK-14172
> URL: https://issues.apache.org/jira/browse/SPARK-14172
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Yingji Zhang
>Priority: Critical
>
> When the hive sql contains nondeterministic fields, spark plan will not push
> down the partition predicate to the HiveTableScan. For example:
> {code}
> -- consider following query which uses a random function to sample rows
> SELECT *
> FROM table_a
> WHERE partition_col = 'some_value'
> AND rand() < 0.01;
> {code}
> The spark plan will not push down the partition predicate to HiveTableScan
> which ends up scanning all partitions data from the table.
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[jira] [Comment Edited] (SPARK-14172) Hive table partition predicate not passed down correctly
[
https://issues.apache.org/jira/browse/SPARK-14172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16189481#comment-16189481
]
Saktheesh Balaraj edited comment on SPARK-14172 at 10/3/17 10:06 AM:
-
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
{noformat}
sqlContext.sql("select * from tableA a, tableB b where
a.trans_date=b.trans_date and a.trans_hour=b.trans_hour")
{noformat}
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1:
{noformat} select trans_date and a.trans_hour from table B {noformat}
step2:
{noformat} select * from tableA where trans_date= and
a.trans_hour = {noformat}
was (Author: saktheesh):
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
{noformat}
sqlContext.sql("select * from tableA a, tableB b where
a.trans_date=b.trans_date and a.trans_hour=b.trans_hour")
{noformat}
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
> Hive table partition predicate not passed down correctly
>
>
> Key: SPARK-14172
> URL: https://issues.apache.org/jira/browse/SPARK-14172
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Yingji Zhang
>Priority: Critical
>
> When the hive sql contains nondeterministic fields, spark plan will not push
> down the partition predicate to the HiveTableScan. For example:
> {code}
> -- consider following query which uses a random function to sample rows
> SELECT *
> FROM table_a
> WHERE partition_col = 'some_value'
> AND rand() < 0.01;
> {code}
> The spark plan will not push down the partition predicate to HiveTableScan
> which ends up scanning all partitions data from the table.
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[jira] [Comment Edited] (SPARK-14172) Hive table partition predicate not passed down correctly
[
https://issues.apache.org/jira/browse/SPARK-14172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16189481#comment-16189481
]
Saktheesh Balaraj edited comment on SPARK-14172 at 10/3/17 10:06 AM:
-
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
{noformat}
sqlContext.sql("select * from tableA a, tableB b where
a.trans_date=b.trans_date and a.trans_hour=b.trans_hour")
{noformat}
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
was (Author: saktheesh):
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
*select * from tableA a, tableB b where a.trans_date=b.trans_date and
a.trans_hour=b.trans_hour;*
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
> Hive table partition predicate not passed down correctly
>
>
> Key: SPARK-14172
> URL: https://issues.apache.org/jira/browse/SPARK-14172
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Yingji Zhang
>Priority: Critical
>
> When the hive sql contains nondeterministic fields, spark plan will not push
> down the partition predicate to the HiveTableScan. For example:
> {code}
> -- consider following query which uses a random function to sample rows
> SELECT *
> FROM table_a
> WHERE partition_col = 'some_value'
> AND rand() < 0.01;
> {code}
> The spark plan will not push down the partition predicate to HiveTableScan
> which ends up scanning all partitions data from the table.
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[jira] [Comment Edited] (SPARK-14172) Hive table partition predicate not passed down correctly
[
https://issues.apache.org/jira/browse/SPARK-14172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16189481#comment-16189481
]
Saktheesh Balaraj edited comment on SPARK-14172 at 10/3/17 9:52 AM:
Similar problem is observed while joining 2 hive tables based on partition
columns.
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
*select * from tableA a, tableB b where a.trans_date=b.trans_date and
a.trans_hour=b.trans_hour;*
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
was (Author: saktheesh):
Similar problem is observed while joining 2 hive tables based on partition
columns.
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
*select * from tableA a, tableB b where a.trans_date=b.trans_date and
a.trans_hour=b.trans_hour;*
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround: *
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
> Hive table partition predicate not passed down correctly
>
>
> Key: SPARK-14172
> URL: https://issues.apache.org/jira/browse/SPARK-14172
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Yingji Zhang
>Priority: Critical
>
> When the hive sql contains nondeterministic fields, spark plan will not push
> down the partition predicate to the HiveTableScan. For example:
> {code}
> -- consider following query which uses a random function to sample rows
> SELECT *
> FROM table_a
> WHERE partition_col = 'some_value'
> AND rand() < 0.01;
> {code}
> The spark plan will not push down the partition predicate to HiveTableScan
> which ends up scanning all partitions data from the table.
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[jira] [Comment Edited] (SPARK-14172) Hive table partition predicate not passed down correctly
[
https://issues.apache.org/jira/browse/SPARK-14172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16189481#comment-16189481
]
Saktheesh Balaraj edited comment on SPARK-14172 at 10/3/17 9:52 AM:
Similar problem is observed while joining 2 hive tables based on partition
columns in Spark
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
*select * from tableA a, tableB b where a.trans_date=b.trans_date and
a.trans_hour=b.trans_hour;*
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
was (Author: saktheesh):
Similar problem is observed while joining 2 hive tables based on partition
columns.
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
*select * from tableA a, tableB b where a.trans_date=b.trans_date and
a.trans_hour=b.trans_hour;*
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround*
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
> Hive table partition predicate not passed down correctly
>
>
> Key: SPARK-14172
> URL: https://issues.apache.org/jira/browse/SPARK-14172
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Yingji Zhang
>Priority: Critical
>
> When the hive sql contains nondeterministic fields, spark plan will not push
> down the partition predicate to the HiveTableScan. For example:
> {code}
> -- consider following query which uses a random function to sample rows
> SELECT *
> FROM table_a
> WHERE partition_col = 'some_value'
> AND rand() < 0.01;
> {code}
> The spark plan will not push down the partition predicate to HiveTableScan
> which ends up scanning all partitions data from the table.
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[jira] [Commented] (SPARK-14172) Hive table partition predicate not passed down correctly
[
https://issues.apache.org/jira/browse/SPARK-14172?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16189481#comment-16189481
]
Saktheesh Balaraj commented on SPARK-14172:
---
Similar problem is observed while joining 2 hive tables based on partition
columns.
*Example*
Table A having 1000 partitions (date partition and hour sub-partition) and
Table B having 2 partition. when joining 2 tables based on partition it's going
for full table scan in table A i.e using all 1000 partitions instead of taking
2 partitions from Table A and join with Table B.
*select * from tableA a, tableB b where a.trans_date=b.trans_date and
a.trans_hour=b.trans_hour;*
(Here trans_date is the partition and trans_hour is the sub-partition on both
the tables)
*Workaround: *
selecting 2 partitions from table B and then do lookup on Table A
step1: select trans_date and a.trans_hour from table B
step2: select * from tableA where trans_date= and
a.trans_hour =
> Hive table partition predicate not passed down correctly
>
>
> Key: SPARK-14172
> URL: https://issues.apache.org/jira/browse/SPARK-14172
> Project: Spark
> Issue Type: Bug
> Components: SQL
>Affects Versions: 1.6.1
>Reporter: Yingji Zhang
>Priority: Critical
>
> When the hive sql contains nondeterministic fields, spark plan will not push
> down the partition predicate to the HiveTableScan. For example:
> {code}
> -- consider following query which uses a random function to sample rows
> SELECT *
> FROM table_a
> WHERE partition_col = 'some_value'
> AND rand() < 0.01;
> {code}
> The spark plan will not push down the partition predicate to HiveTableScan
> which ends up scanning all partitions data from the table.
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