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Github user vinodkc commented on the pull request:
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Sure I'll work on SPARK-10631
Thanks
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Github user tnachen commented on the pull request:
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This is only recently merged so this is not yet released, so Mesosphere
DCOS won't able to support Python yet.
And if you wan tot provide s3 you just need to give it
Github user viesti commented on the pull request:
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So gave mesosphere a go (neat that there is a cloudformation template for
that :)), but didn't find a way to tell how to transfer my local program onto
the cluster since
Github user mengxr commented on the pull request:
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LGTM. Merged into master. @vinodkc `values` needs API doc, alone with some
other public methods. I created a JIRA for it:
https://issues.apache.org/jira/browse/SPARK-1063
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@tnachen Thanks for the kind advice! :) I'll have a try, although we found
out that AWS EMR seems to support running Spark also and got an initial hello
world PySpark scr
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Hello!
I was reading the explanation and I'm not quite sure I understand the
reasoning still. I spent a bit too long trying to figure out how to configure
Github user GavinGavinNo1 commented on the pull request:
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@marmbrus Sorry to disturb again. Could you please give me a reply? It's my
first try. Maybe I need some advice.
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Github user lkhamsurenl commented on the pull request:
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Sorry for the late response! I see what you're saying. The difficulty with
that approach I am having is in inside def binSeqOp(agg:
Array[DTStatsAggregator], baggedP
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Github user pallavipr commented on the pull request:
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Looks good Rama. We are almost done with DB2 changes - will send for review
soon.
One question, did you introduce a stringDataType property in connection
url?
Github user XuTingjun commented on the pull request:
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@JoshRosen, Can you have a look on this? Thanks.
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Github user ericl commented on the pull request:
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@mengxr I did the refactoring as suggested
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Github user rxin commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -189,6 +190,14 @@ def approxCountDistinct(col, rsd=None):
return Column(jc)
+@since(1.6)
Github user rxin commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/functions.py ---
@@ -189,6 +190,14 @@ def approxCountDistinct(col, rsd=None):
return Column(jc)
+@since(1.6)
Github user yjshen commented on the pull request:
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@marmbrus converting a filter into CNF may lead to an expanded filter,
which I think is not necessarily a general optimisation.
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--- Diff: docs/sql-programming-guide.md ---
@@ -2261,7 +2261,7 @@ Several caching related features are not supported
yet:
## Compatibility with Apache Hive
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Merged into master. Thanks!
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It has been merged to master.
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Github user vanzin commented on the pull request:
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@rxin I reverted the patch that caused those.
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I've merged this.
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@vanzin do you know what's going on with the tests?
[error] Execution of test test.org.apache.spark.sql.JavaApplySchemaSuite
failed: java.lang.ClassNotFoundExcepti
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Can one of the admins verify this patch?
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GitHub user Jianfeng-chs opened a pull request:
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[SPARK-10577] [PySpark] DataFrame hint for broadcast join
https://issues.apache.org/jira/browse/SPARK-10577
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Github user vanzin commented on the pull request:
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To clarify: the YARN backend also needs to know whether the executor being
killed needs to be replaced or not. Right now, when the executor is not to be
replaced, that's
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Ok, I think I see what the problem is. But your fix is not correct.
The problem is here:
doRequestTotalExecutors(
numExistingExecutors +
Github user yhuai commented on a diff in the pull request:
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--- Diff: docs/sql-programming-guide.md ---
@@ -1954,7 +1954,7 @@ without the need to write any code.
## Running the Thrift JDBC/ODBC server
The
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@zjffdu could you take a look at whether `SparkUI.setAppName` is really
needed at all?
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GitHub user sarutak opened a pull request:
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[SPARK-10584][SQL][DOC] Documentation about the compatible Hive version is
wrong.
In Spark 1.5.0, Spark SQL is compatible with Hive 0.12.0 through 1.2.1 but
the documentation is wrong.
/CC
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O.K. I'll do it.
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