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Apache Spark reassigned SPARK-15672:
Assignee: Apache Spark
> R programming guide update
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Apache Spark commented on SPARK-15672:
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User 'vectorijk' has created a pull request
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Aamir Abbas commented on SPARK-15919:
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Thank you for the response.
If I generate new
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Marco Capuccini updated SPARK-15941:
Summary: Netty RPC implementation ignores the executor bind address (was:
Spark executor a
Marco Capuccini created SPARK-15941:
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Summary: Spark executor address always bind to IP address when
using Netty RPC implementation
Key: SPARK-15941
URL: https://issues.apache.org/jira/browse/SPARK-15941
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Sean Owen commented on SPARK-15919:
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This is still wrong because you establish the path
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Sean Owen edited comment on SPARK-15919 at 6/14/16 9:54 AM:
H
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Aamir Abbas edited comment on SPARK-15919 at 6/14/16 9:49 AM:
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Aamir Abbas commented on SPARK-15919:
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Here's the updated code, after using foreachRD
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Apache Spark commented on SPARK-15937:
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User 'subrotosanyal' has created a pull requ
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Sean Owen resolved SPARK-15936.
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Resolution: Duplicate
> CLONE - Add class weights to Random Forest
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Sean Owen commented on SPARK-15930:
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Yes, you already have that information, but I can
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Sean Owen resolved SPARK-15940.
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Resolution: Not A Problem
Multiple Spark contexts are not supported.
> Simultaneous multiple spark c
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Sean Owen closed SPARK-15919.
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> DStream "saveAsTextFile" doesn't update the prefix after each checkpoint
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Jeff Zhang commented on SPARK-15930:
I see, I guess you are trying to get the total n
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yuhao yang commented on SPARK-15930:
We need the size of input dataset to calculate r
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Sean Owen resolved SPARK-15919.
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Resolution: Not A Problem
Do _not_ reopen this JIRA. You would only do so if the conversation has
me
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Sean Owen commented on SPARK-15930:
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The sum of all frequencies from freqItemSets is no
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Jeff Zhang commented on SPARK-15930:
Don't we can get the count from freqItemsets in
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marymwu commented on SPARK-15802:
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We still have a question. How to use "binary" protocol
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Ismael Juma commented on SPARK-12177:
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{quote}
b) the real benefit is security - I am
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Aamir Abbas reopened SPARK-15919:
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I tried the solution you mentioned. It didn't work.
I applied foreachRDD, and added a random number
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Sean Owen commented on SPARK-15930:
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What's the use case for this? the FP growth output
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Piotr Milanowski commented on SPARK-15345:
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[~hvanhovell] Thanks, I corrected it
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Apache Spark reassigned SPARK-15939:
Assignee: (was: Apache Spark)
> Clarify ml.linalg usage
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Apache Spark reassigned SPARK-15939:
Assignee: Apache Spark
> Clarify ml.linalg usage
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Apache Spark commented on SPARK-15939:
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User 'zhengruifeng' has created a pull reque
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zhengruifeng updated SPARK-15939:
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Description:
1, update comments in {{pyspark.ml}} that it use {{ml.linalg}} not
{{mllib.linalg}}
Partha Pratim Ghosh created SPARK-15940:
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Summary: Simultaneous multiple spark context with different
kerberos FID credentials from within one id
Key: SPARK-15940
URL: https://issues.apache.org/jira/browse/S
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zhengruifeng updated SPARK-15939:
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Description:
1, update comments in {{pyspark.ml}} that it use {ml.linalg} not {mllib.linalg}
2, r
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Piotr Milanowski edited comment on SPARK-15345 at 6/14/16 7:34 AM:
zhengruifeng created SPARK-15939:
Summary: Clarify ml.linalg usage
Key: SPARK-15939
URL: https://issues.apache.org/jira/browse/SPARK-15939
Project: Spark
Issue Type: Improvement
Com
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Piotr Milanowski edited comment on SPARK-15345 at 6/14/16 7:32 AM:
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Apache Spark reassigned SPARK-15938:
Assignee: Apache Spark
> Adding "support" property to MLlib Association Rule
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Apache Spark reassigned SPARK-15938:
Assignee: (was: Apache Spark)
> Adding "support" property to MLlib Association Rule
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Apache Spark commented on SPARK-15938:
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User 'hhbyyh' has created a pull request for
yuhao yang created SPARK-15938:
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Summary: Adding "support" property to MLlib Association Rule
Key: SPARK-15938
URL: https://issues.apache.org/jira/browse/SPARK-15938
Project: Spark
Issue Type: I
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Subroto Sanyal updated SPARK-15937:
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Description:
h5. Problem:
Spark Job fails in yarn-cluster mode if the job takes less time tha
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Subroto Sanyal updated SPARK-15937:
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Priority: Critical (was: Major)
> Spark declares a succeeding job to be failed in yarn-clust
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