Sathiya Kumar created SPARK-22181:
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Summary: ReplaceExceptWithNotFilter if one or both of the datasets
are fully derived out of Filters from a same parent
Key: SPARK-22181
URL:
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Sathiya Kumar commented on SPARK-22080:
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Here is a PR with the proposed changes:
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Sathiya Kumar updated SPARK-22080:
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Description: [SPARK-9843] added support for adding custom rules for
optimising LogicalPlan,
Sathiya Kumar created SPARK-22080:
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Summary: Allow developers to add pre-optimisation rules
Key: SPARK-22080
URL: https://issues.apache.org/jira/browse/SPARK-22080
Project: Spark
Issue Type:
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https://issues.apache.org/jira/browse/SPARK-20589?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=16129289#comment-16129289
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Amit Kumar commented on SPARK-20589:
As you said, adding job boundary via code will be much easier
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Amit Kumar commented on SPARK-20589:
[~imranr] Like you said, we could restrict the number of
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Amit Kumar commented on SPARK-20589:
I can probably give more reference. This originally arose from
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amit kumar closed SPARK-20671.
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Resolution: Not A Problem
My Bad . I configured it wrong. setMaster("local[*]") in place of
amit kumar created SPARK-20671:
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Summary: Processing muitple kafka topics with single spark
streaming context hangs on batchSubmitted.
Key: SPARK-20671
URL: https://issues.apache.org/jira/browse/SPARK-20671
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Abhishek Kumar updated SPARK-12180:
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Comment: was deleted
(was: Is there any concrete solution or reason explaining the issue ? I
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Abhishek Kumar edited comment on SPARK-12180 at 3/9/17 2:52 AM:
Is there
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Abhishek Kumar commented on SPARK-12180:
Is there any concrete solution or reason explaining the
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Ashok Kumar updated SPARK-19255:
Description:
Since its difficult to load huge dataset, below steps will help in reproducing
the
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Ashok Kumar updated SPARK-19255:
Summary: SQL Listener is causing out of memory, in case of data size is in
petabytes. (was: SQL
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Ashok Kumar commented on SPARK-19255:
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@Sean
I will put my scenario in another way.
Assume each data
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Ashok Kumar commented on SPARK-19255:
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@Takeshi , thanks for looking into the issue.
You are right,
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Ashok Kumar updated SPARK-19255:
Attachment: spark_sqllistener_oom.png
Attached snapshot is heap dump profiled by eclipse mat
>
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Ashok Kumar commented on SPARK-19255:
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Due to issue, i am not able to attach screenshot. I will
Ashok Kumar created SPARK-19255:
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Summary: SQL Listener is causing out of memory, in case of large
no of shuffle partition
Key: SPARK-19255
URL: https://issues.apache.org/jira/browse/SPARK-19255
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Sameer Kumar commented on SPARK-18986:
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Shouldn't the priority be increased for this because I am
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Sumesh Kumar commented on SPARK-18200:
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Thanks much [~dongjoon]
> GraphX Invalid initial capacity
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Sumesh Kumar commented on SPARK-18200:
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Does this issue exist currently in version 2.0.1?. I just
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Bipul Kumar commented on SPARK-18489:
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ok. Thanks Herman. I ll have a look on the changes.
>
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Bipul Kumar commented on SPARK-18489:
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[~hvanhovell]
Will this change cover all the operators
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Bipul Kumar edited comment on SPARK-18489 at 11/17/16 11:35 AM:
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Bipul Kumar updated SPARK-18489:
Comment: was deleted
(was: [~prashant_] please review this.)
> Implicit type conversion during
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Bipul Kumar commented on SPARK-18489:
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[~prashant_] please review this.
> Implicit type conversion
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Bipul Kumar commented on SPARK-18489:
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[~prashant_] please review this.
> Implicit type conversion
Bipul Kumar created SPARK-18489:
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Summary: Implicit type conversion during comparision between
Integer type column and String type column
Key: SPARK-18489
URL: https://issues.apache.org/jira/browse/SPARK-18489
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Sunil Kumar commented on SPARK-18150:
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I am using Spark : 2.0.0.24 and spark-avro : 2.11-3.0.1.
>
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Sunil Kumar updated SPARK-18150:
Description:
I am using Apache Spark 2.0.1 for processing the Grid HDFS Avro file, however I
Sunil Kumar created SPARK-18154:
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Summary: CLONE - Change Source API so that sources do not need to
keep unbounded state
Key: SPARK-18154
URL: https://issues.apache.org/jira/browse/SPARK-18154
Project:
Sunil Kumar created SPARK-18151:
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Summary: CLONE - MetadataLog should support purging old logs
Key: SPARK-18151
URL: https://issues.apache.org/jira/browse/SPARK-18151
Project: Spark
Issue
Sunil Kumar created SPARK-18155:
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Summary: CLONE - HDFSMetadataLog should not leak CRC files
Key: SPARK-18155
URL: https://issues.apache.org/jira/browse/SPARK-18155
Project: Spark
Issue Type:
Sunil Kumar created SPARK-18152:
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Summary: CLONE - FileStreamSource should not track the list of
seen files indefinitely
Key: SPARK-18152
URL: https://issues.apache.org/jira/browse/SPARK-18152
Project:
Sunil Kumar created SPARK-18150:
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Summary: Spark 2.* failes to create partitions for avro files
Key: SPARK-18150
URL: https://issues.apache.org/jira/browse/SPARK-18150
Project: Spark
Issue
Sunil Kumar created SPARK-18157:
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Summary: CLONE - Support purging aged file entry for
FileStreamSource metadata log
Key: SPARK-18157
URL: https://issues.apache.org/jira/browse/SPARK-18157
Project:
Sunil Kumar created SPARK-18156:
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Summary: CLONE - StreamExecution should discard unneeded metadata
Key: SPARK-18156
URL: https://issues.apache.org/jira/browse/SPARK-18156
Project: Spark
Issue
Sunil Kumar created SPARK-18153:
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Summary: CLONE - Ability to remove old metadata for structure
streaming MetadataLog
Key: SPARK-18153
URL: https://issues.apache.org/jira/browse/SPARK-18153
Project:
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sriram kumar updated SPARK-17973:
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Description:
i cannot able to split Dataset exactly with condition. i have a scenario where
i
sriram kumar created SPARK-17973:
Summary: is there any way to split Dataset into 2 or more based on
the given condition
Key: SPARK-17973
URL: https://issues.apache.org/jira/browse/SPARK-17973
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Tarun Kumar edited comment on SPARK-16575 at 10/14/16 8:38 AM:
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[~rxin] I
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Tarun Kumar commented on SPARK-16575:
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[~rxin] I have now added the support of openCostInBytes,
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karan kumar commented on SPARK-4105:
I also ran into this error :java.io.IOException:
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Yashwanth Kumar edited comment on SPARK-10697 at 9/7/16 9:33 AM:
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Yes
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Yashwanth Kumar edited comment on SPARK-10697 at 9/7/16 9:19 AM:
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As
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Yashwanth Kumar reopened SPARK-10697:
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As discussed, Rule is one of the necessary measure that eliminates the concern
of random
Manoj Kumar created SPARK-17146:
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Summary: Add RandomizedSearch to the CrossValidator API
Key: SPARK-17146
URL: https://issues.apache.org/jira/browse/SPARK-17146
Project: Spark
Issue Type:
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Manoj Kumar commented on SPARK-17116:
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Haha, not really. I just found it odd that setParams accepts
Manoj Kumar created SPARK-17118:
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Summary: Make examples Python3 compatible
Key: SPARK-17118
URL: https://issues.apache.org/jira/browse/SPARK-17118
Project: Spark
Issue Type: Improvement
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Manoj Kumar updated SPARK-17116:
Description:
Currently, it is possible to override the default params set at constructor
time by
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Manoj Kumar edited comment on SPARK-17116 at 8/17/16 10:17 PM:
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[~josephkb]
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Manoj Kumar commented on SPARK-17116:
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[~josephkb] [~mlnick]
This is not super important, but I do
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Manoj Kumar updated SPARK-17116:
Summary: Allow params to be a {string, value} dict at fit time (was: Allow
params to be a
Manoj Kumar created SPARK-17116:
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Summary: Allow params to be a {string, value} dict
Key: SPARK-17116
URL: https://issues.apache.org/jira/browse/SPARK-17116
Project: Spark
Issue Type:
Naveen Kumar created SPARK-16585:
Summary: Update inner fields of complex types in dataframes
Key: SPARK-16585
URL: https://issues.apache.org/jira/browse/SPARK-16585
Project: Spark
Issue
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Sunil Kumar commented on SPARK-15347:
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Hi ,
Is there any plan to fix this issue in Spark-SQL and
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Manoj Kumar commented on SPARK-16365:
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Could you be a bit more clearer about the first point? Is it
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Manoj Kumar commented on SPARK-3728:
Hi [~xusen]. Are you still working on this?
> RandomForest:
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Manoj Kumar commented on SPARK-16365:
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Is the ultimate aim to make mllib-local, the scikit-learn of
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Manoj Kumar commented on SPARK-16399:
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It would just run with the default python, that is in this
Manoj Kumar created SPARK-16399:
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Summary: Set PYSPARK_PYTHON to point to "python" instead of
"python2.7"
Key: SPARK-16399
URL: https://issues.apache.org/jira/browse/SPARK-16399
Project: Spark
Manoj Kumar created SPARK-16307:
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Summary: Improve testing for DecisionTree variances
Key: SPARK-16307
URL: https://issues.apache.org/jira/browse/SPARK-16307
Project: Spark
Issue Type: Test
Manoj Kumar created SPARK-16306:
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Summary: Improve testing for DecisionTree variances
Key: SPARK-16306
URL: https://issues.apache.org/jira/browse/SPARK-16306
Project: Spark
Issue Type: Test
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Manish Kumar updated SPARK-15666:
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Comment: was deleted
(was: [~hvanhovell] by saying that underlying plan is broken, you mean
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Manish Kumar edited comment on SPARK-16169 at 6/24/16 9:14 AM:
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Even if our
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Manish Kumar commented on SPARK-16169:
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Even if our code is asking to do more work then some task
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Manoj Kumar edited comment on SPARK-14351 at 6/23/16 11:43 PM:
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OK, so here
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Manoj Kumar edited comment on SPARK-14351 at 6/23/16 11:43 PM:
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OK, so here
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Manish Kumar commented on SPARK-16169:
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Hi [~srowen]
I am not saying it is taking 5 minutes longer
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Manish Kumar edited comment on SPARK-16169 at 6/23/16 10:58 AM:
Hi
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Manish Kumar updated SPARK-16169:
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Description:
When a spark application is (written in scala) trying to save intermediate
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Manish Kumar updated SPARK-16169:
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Description:
When a spark application is (written in scala) trying to save intermediate
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Manish Kumar updated SPARK-16169:
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Description:
When a spark application is (written in scala) trying to save intermediate
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Manish Kumar updated SPARK-16169:
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Description:
When a spark application is (written in scala) trying to save intermediate
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Manish Kumar updated SPARK-16169:
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Attachment: Spark-UI.png
> Saving Intermediate dataframe increasing processing time upto 5
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Manish Kumar updated SPARK-16169:
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Description:
When a spark application is written in scala trying to save intermediate
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Manish Kumar updated SPARK-16169:
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Description:
When a spark application is (written in scala) trying to save intermediate
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Manish Kumar updated SPARK-16169:
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Description:
When, a spark application written in scala trying to save intermediate
dataframe,
Manish Kumar created SPARK-16169:
Summary: Saving Intermediate dataframe increasing processing time
upto 5 times.
Key: SPARK-16169
URL: https://issues.apache.org/jira/browse/SPARK-16169
Project:
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Manoj Kumar updated SPARK-14351:
Comment: was deleted
(was: Here are my thoughts: Also ccing [~sethah] since he has seen this part
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Manoj Kumar commented on SPARK-14351:
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Here are my thoughts: Also ccing [~sethah] since he has seen
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Manish Kumar commented on SPARK-15666:
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[~hvanhovell] by saying that underlying plan is broken, you
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Manish Kumar edited comment on SPARK-15666 at 6/20/16 1:14 PM:
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Hi
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Manish Kumar commented on SPARK-15666:
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Hi Herman,
I haven't checked it on 2.0. But even if it
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Manoj Kumar commented on SPARK-14351:
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OK, so here are some benchmarks that validate your claims
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Manoj Kumar commented on SPARK-14351:
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I can try working on this.
> Optimize ImpurityAggregator for
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Manoj Kumar edited comment on SPARK-3155 at 6/14/16 5:01 AM:
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1. I agree that
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Manoj Kumar commented on SPARK-3155:
1. I agree that the use cases are limited to single trees. You
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Manoj Kumar commented on SPARK-3155:
I would like to add support for pruning DecisionTrees as part of
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Manoj Kumar updated SPARK-3155:
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Comment: was deleted
(was: I would like to add support for pruning DecisionTrees as part of my
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https://issues.apache.org/jira/browse/SPARK-3155?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15328487#comment-15328487
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Manoj Kumar commented on SPARK-3155:
I would like to add support for pruning DecisionTrees as part of
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https://issues.apache.org/jira/browse/SPARK-9623?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15319450#comment-15319450
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Manoj Kumar commented on SPARK-9623:
[~yanboliang] Are you still working on this? Would you mind if I
Manoj Kumar created SPARK-15761:
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Summary: pyspark shell should load if PYSPARK_DRIVER_PYTHON is
ipython an Python3
Key: SPARK-15761
URL: https://issues.apache.org/jira/browse/SPARK-15761
Project:
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https://issues.apache.org/jira/browse/SPARK-15666?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15310134#comment-15310134
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Manish Kumar commented on SPARK-15666:
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Can someone please look into this issue? As this blocking
Manish Kumar created SPARK-15666:
Summary: Join on two tables generated from a same table throwing
query analyzer issue
Key: SPARK-15666
URL: https://issues.apache.org/jira/browse/SPARK-15666
Ajesh Kumar created SPARK-15503:
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Summary: Not able to join two hive tables having partition using
HiveContext.sql
Key: SPARK-15503
URL: https://issues.apache.org/jira/browse/SPARK-15503
Project: Spark
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https://issues.apache.org/jira/browse/SPARK-13699?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15272123#comment-15272123
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Manish Kumar commented on SPARK-13699:
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Hi,
Even I am facing a similar issue with overwrite mode. I
Pavan Kumar created SPARK-14266:
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Summary: Association with remote system
[akka.tcp://sparkDriver@192.168.1.81:34047] has failed, address is now gated
for [5000] ms. Reason is: [Association failed$
Key: SPARK-14266
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https://issues.apache.org/jira/browse/SPARK-5433?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=15194722#comment-15194722
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Geet Kumar commented on SPARK-5433:
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The spark-ec2 script does not mount disks for the d2.xlarge
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