[jira] [Comment Edited] (SPARK-22814) JDBC support date/timestamp type as partitionColumn
[ https://issues.apache.org/jira/browse/SPARK-22814?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16833145#comment-16833145 ] Al Johri edited comment on SPARK-22814 at 5/4/19 7:37 PM: -- Cross posting my Github [comment|https://github.com/apache/spark/pull/21834#issuecomment-489357987] here: looks like this feature does not work with PySpark 2.4.0. was (Author: al.johri): Cross posting my Github [comment]([https://github.com/apache/spark/pull/21834#issuecomment-489357987]) here: looks like this feature does not work with PySpark 2.4.0. > JDBC support date/timestamp type as partitionColumn > --- > > Key: SPARK-22814 > URL: https://issues.apache.org/jira/browse/SPARK-22814 > Project: Spark > Issue Type: Improvement > Components: SQL >Affects Versions: 1.6.2, 2.2.1 >Reporter: Yuechen Chen >Assignee: Takeshi Yamamuro >Priority: Major > Fix For: 2.4.0 > > Original Estimate: 168h > Remaining Estimate: 168h > > In spark, you can partition MySQL queries by partitionColumn. > val df = (spark.read.jdbc(url=jdbcUrl, > table="employees", > columnName="emp_no", > lowerBound=1L, > upperBound=10L, > numPartitions=100, > connectionProperties=connectionProperties)) > display(df) > But, partitionColumn must be a numeric column from the table. > However, there are lots of table, which has no primary key, and has some > date/timestamp indexes. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-22814) JDBC support date/timestamp type as partitionColumn
[ https://issues.apache.org/jira/browse/SPARK-22814?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16833145#comment-16833145 ] Al Johri commented on SPARK-22814: -- Cross posting my Github [comment]([https://github.com/apache/spark/pull/21834#issuecomment-489357987]) here: looks like this feature does not work with PySpark 2.4.0. > JDBC support date/timestamp type as partitionColumn > --- > > Key: SPARK-22814 > URL: https://issues.apache.org/jira/browse/SPARK-22814 > Project: Spark > Issue Type: Improvement > Components: SQL >Affects Versions: 1.6.2, 2.2.1 >Reporter: Yuechen Chen >Assignee: Takeshi Yamamuro >Priority: Major > Fix For: 2.4.0 > > Original Estimate: 168h > Remaining Estimate: 168h > > In spark, you can partition MySQL queries by partitionColumn. > val df = (spark.read.jdbc(url=jdbcUrl, > table="employees", > columnName="emp_no", > lowerBound=1L, > upperBound=10L, > numPartitions=100, > connectionProperties=connectionProperties)) > display(df) > But, partitionColumn must be a numeric column from the table. > However, there are lots of table, which has no primary key, and has some > date/timestamp indexes. -- This message was sent by Atlassian JIRA (v7.6.3#76005) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-13330) PYTHONHASHSEED is not propgated to python worker
[
https://issues.apache.org/jira/browse/SPARK-13330?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15996217#comment-15996217
]
Al Johri commented on SPARK-13330:
--
Can this be backported to 2.0 or 2.1? I'm having trouble using Python 3 on
spark at the moment. Currently I have to set
`SPARK_YARN_USER_ENV=PYTHONHASHSEED=0` before running spark-submit. Until 2.2
is released, would it be best practice to put this variable into spark-env.sh?
> PYTHONHASHSEED is not propgated to python worker
>
>
> Key: SPARK-13330
> URL: https://issues.apache.org/jira/browse/SPARK-13330
> Project: Spark
> Issue Type: Bug
> Components: PySpark
>Affects Versions: 1.6.0
>Reporter: Jeff Zhang
>Assignee: Jeff Zhang
> Fix For: 2.2.0
>
>
> when using python 3.3 , PYTHONHASHSEED is only set in driver, but not
> propagated to executor, and cause the following error.
> {noformat}
> File "/Users/jzhang/github/spark/python/pyspark/rdd.py", line 74, in
> portable_hash
> raise Exception("Randomness of hash of string should be disabled via
> PYTHONHASHSEED")
> Exception: Randomness of hash of string should be disabled via PYTHONHASHSEED
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
> at
> org.apache.spark.api.python.PythonRunner$$anon$1.(PythonRDD.scala:207)
> at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
> at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
> at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:342)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:313)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:277)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:77)
> at
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:45)
> at org.apache.spark.scheduler.Task.run(Task.scala:81)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> {noformat}
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