[jira] [Created] (SPARK-10522) Nanoseconds part of Timestamp should be positive in parquet

Davies Liu created SPARK-10522: -- Summary: Nanoseconds part of Timestamp should be positive in parquet Key: SPARK-10522 URL: https://issues.apache.org/jira/browse/SPARK-10522 Project: Spark

[jira] [Commented] (SPARK-10066) Can't create HiveContext with spark-shell or spark-sql on snapshot

[ https://issues.apache.org/jira/browse/SPARK-10066?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737747#comment-14737747 ] Robert Beauchemin commented on SPARK-10066: --- After upgrading to Spark 1.5 release version (and

[jira] [Resolved] (SPARK-7736) Exception not failing Python applications (in yarn cluster mode)

[ https://issues.apache.org/jira/browse/SPARK-7736?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Marcelo Vanzin resolved SPARK-7736. --- Resolution: Fixed Fix Version/s: 1.5.1 > Exception not failing Python applications (in

[jira] [Commented] (SPARK-10439) Catalyst should check for overflow / underflow of date and timestamp values

[ https://issues.apache.org/jira/browse/SPARK-10439?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737772#comment-14737772 ] Marcelo Vanzin commented on SPARK-10439: Davies filed SPARK-10522 to track the negative

[jira] [Updated] (SPARK-10523) SparkR formula syntax to turn strings/factors into numerics

[ https://issues.apache.org/jira/browse/SPARK-10523?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Vincent Warmerdam updated SPARK-10523: -- Description: In normal (non SparkR) R the formula syntax enables strings or factors to

[jira] [Updated] (SPARK-10523) SparkR formula syntax to turn strings/factors into numerics

[ https://issues.apache.org/jira/browse/SPARK-10523?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Vincent Warmerdam updated SPARK-10523: -- Description: In normal (non SparkR) R the formula syntax enables strings or factors to

[jira] [Created] (SPARK-10524) Decision tree binary classification with ordered categorical features: incorrect centroid

Joseph K. Bradley created SPARK-10524: - Summary: Decision tree binary classification with ordered categorical features: incorrect centroid Key: SPARK-10524 URL:

[jira] [Commented] (SPARK-10312) Enhance SerDe to handle atomic vector

[ https://issues.apache.org/jira/browse/SPARK-10312?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737919#comment-14737919 ] Shivaram Venkataraman commented on SPARK-10312: --- Is this covered by

[jira] [Created] (SPARK-10525) Add Python example for VectorSlicer to user guide

Joseph K. Bradley created SPARK-10525: - Summary: Add Python example for VectorSlicer to user guide Key: SPARK-10525 URL: https://issues.apache.org/jira/browse/SPARK-10525 Project: Spark

[jira] [Resolved] (SPARK-9772) Add Python API, user guide and example for ml.feature.VectorSlicer

[ https://issues.apache.org/jira/browse/SPARK-9772?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joseph K. Bradley resolved SPARK-9772. -- Resolution: Fixed Fix Version/s: 1.6.0 Issue resolved by pull request 8102

[jira] [Commented] (SPARK-10525) Add Python example for VectorSlicer to user guide

[ https://issues.apache.org/jira/browse/SPARK-10525?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737926#comment-14737926 ] Joseph K. Bradley commented on SPARK-10525: --- [~yanboliang] Would you mind adding this? Thanks!

[jira] [Updated] (SPARK-9772) Add Python API for ml.feature.VectorSlicer

[ https://issues.apache.org/jira/browse/SPARK-9772?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joseph K. Bradley updated SPARK-9772: - Summary: Add Python API for ml.feature.VectorSlicer (was: Add Python API, user guide and

[jira] [Updated] (SPARK-9718) LinearRegressionTrainingSummary should hold all columns in transformed data

[ https://issues.apache.org/jira/browse/SPARK-9718?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joseph K. Bradley updated SPARK-9718: - Shepherd: Joseph K. Bradley Assignee: holdenk Target Version/s:

[jira] [Commented] (SPARK-9273) Add Convolutional Neural network to Spark MLlib

[ https://issues.apache.org/jira/browse/SPARK-9273?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737948#comment-14737948 ] Alexander Ulanov commented on SPARK-9273: - Hi Yuhao! I have few comments regarding the interface

[jira] [Comment Edited] (SPARK-9273) Add Convolutional Neural network to Spark MLlib

[ https://issues.apache.org/jira/browse/SPARK-9273?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737948#comment-14737948 ] Alexander Ulanov edited comment on SPARK-9273 at 9/10/15 1:18 AM: -- Hi

[jira] [Commented] (SPARK-10276) Add @since annotation to pyspark.mllib.recommendation

[ https://issues.apache.org/jira/browse/SPARK-10276?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738002#comment-14738002 ] Yu Ishikawa commented on SPARK-10276: - It seems that `@since` depends on an order of decorators.

[jira] [Updated] (SPARK-9772) Add Python API, user guide and example for ml.feature.VectorSlicer

[ https://issues.apache.org/jira/browse/SPARK-9772?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joseph K. Bradley updated SPARK-9772: - Shepherd: Joseph K. Bradley Assignee: Yanbo Liang Target

[jira] [Commented] (SPARK-10312) Enhance SerDe to handle atomic vector

[ https://issues.apache.org/jira/browse/SPARK-10312?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737921#comment-14737921 ] Sun Rui commented on SPARK-10312: - No. > Enhance SerDe to handle atomic vector >

[jira] [Created] (SPARK-10526) Display cores/memory on ExecutorsTab

Jeff Zhang created SPARK-10526: -- Summary: Display cores/memory on ExecutorsTab Key: SPARK-10526 URL: https://issues.apache.org/jira/browse/SPARK-10526 Project: Spark Issue Type: Improvement

[jira] [Assigned] (SPARK-9078) Use of non-standard LIMIT keyword in JDBC tableExists code

[ https://issues.apache.org/jira/browse/SPARK-9078?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-9078: --- Assignee: (was: Apache Spark) > Use of non-standard LIMIT keyword in JDBC tableExists

[jira] [Commented] (SPARK-9078) Use of non-standard LIMIT keyword in JDBC tableExists code

[ https://issues.apache.org/jira/browse/SPARK-9078?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738011#comment-14738011 ] Apache Spark commented on SPARK-9078: - User 'sureshthalamati' has created a pull request for this

[jira] [Commented] (SPARK-10523) SparkR formula syntax to turn strings/factors into numerics

[ https://issues.apache.org/jira/browse/SPARK-10523?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737960#comment-14737960 ] Eric Liang commented on SPARK-10523: We can convert to boolean easily enough, but supporting >2

[jira] [Closed] (SPARK-6697) PeriodicGraphCheckpointer is not clear edges.

[ https://issues.apache.org/jira/browse/SPARK-6697?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Joseph K. Bradley closed SPARK-6697. Resolution: Not A Problem I'm going to close this for now since it's not really a bug, just

[jira] [Commented] (SPARK-9273) Add Convolutional Neural network to Spark MLlib

[ https://issues.apache.org/jira/browse/SPARK-9273?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737963#comment-14737963 ] yuhao yang commented on SPARK-9273: --- Thank a lot for your attention [~avulanov]. I do hope we can join

[jira] [Assigned] (SPARK-10526) Display cores/memory on ExecutorsTab

[ https://issues.apache.org/jira/browse/SPARK-10526?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10526: Assignee: (was: Apache Spark) > Display cores/memory on ExecutorsTab >

[jira] [Commented] (SPARK-10526) Display cores/memory on ExecutorsTab

[ https://issues.apache.org/jira/browse/SPARK-10526?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738167#comment-14738167 ] Apache Spark commented on SPARK-10526: -- User 'zjffdu' has created a pull request for this issue:

[jira] [Assigned] (SPARK-10526) Display cores/memory on ExecutorsTab

[ https://issues.apache.org/jira/browse/SPARK-10526?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10526: Assignee: Apache Spark > Display cores/memory on ExecutorsTab >

[jira] [Created] (SPARK-10530) Kill other task attempts when one taskattempt belonging the same task is succeeded in speculation

Jeff Zhang created SPARK-10530: -- Summary: Kill other task attempts when one taskattempt belonging the same task is succeeded in speculation Key: SPARK-10530 URL: https://issues.apache.org/jira/browse/SPARK-10530

[jira] [Commented] (SPARK-10516) Add values as a property to DenseVector in PySpark

[ https://issues.apache.org/jira/browse/SPARK-10516?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738179#comment-14738179 ] Apache Spark commented on SPARK-10516: -- User 'vinodkc' has created a pull request for this issue:

[jira] [Assigned] (SPARK-10516) Add values as a property to DenseVector in PySpark

[ https://issues.apache.org/jira/browse/SPARK-10516?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10516: Assignee: (was: Apache Spark) > Add values as a property to DenseVector in PySpark >

[jira] [Assigned] (SPARK-10516) Add values as a property to DenseVector in PySpark

[ https://issues.apache.org/jira/browse/SPARK-10516?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10516: Assignee: Apache Spark > Add values as a property to DenseVector in PySpark >

[jira] [Assigned] (SPARK-10530) Kill other task attempts when one taskattempt belonging the same task is succeeded in speculation

[ https://issues.apache.org/jira/browse/SPARK-10530?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10530: Assignee: Apache Spark > Kill other task attempts when one taskattempt belonging the same

[jira] [Commented] (SPARK-10530) Kill other task attempts when one taskattempt belonging the same task is succeeded in speculation

[ https://issues.apache.org/jira/browse/SPARK-10530?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738180#comment-14738180 ] Apache Spark commented on SPARK-10530: -- User 'zjffdu' has created a pull request for this issue:

[jira] [Assigned] (SPARK-10530) Kill other task attempts when one taskattempt belonging the same task is succeeded in speculation

[ https://issues.apache.org/jira/browse/SPARK-10530?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10530: Assignee: (was: Apache Spark) > Kill other task attempts when one taskattempt

[jira] [Commented] (SPARK-9790) [YARN] Expose in WebUI if NodeManager is the reason why executors were killed.

[ https://issues.apache.org/jira/browse/SPARK-9790?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738187#comment-14738187 ] Jeff Zhang commented on SPARK-9790: --- Pretty useful feature IMO, any progress on it ? > [YARN] Expose in

[jira] [Assigned] (SPARK-10276) Add @since annotation to pyspark.mllib.recommendation

[ https://issues.apache.org/jira/browse/SPARK-10276?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10276: Assignee: Apache Spark > Add @since annotation to pyspark.mllib.recommendation >

[jira] [Assigned] (SPARK-10276) Add @since annotation to pyspark.mllib.recommendation

[ https://issues.apache.org/jira/browse/SPARK-10276?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10276: Assignee: (was: Apache Spark) > Add @since annotation to pyspark.mllib.recommendation

[jira] [Commented] (SPARK-10276) Add @since annotation to pyspark.mllib.recommendation

[ https://issues.apache.org/jira/browse/SPARK-10276?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738033#comment-14738033 ] Apache Spark commented on SPARK-10276: -- User 'yu-iskw' has created a pull request for this issue:

[jira] [Created] (SPARK-10527) evaluate debugString only when log level is debug

Yash Datta created SPARK-10527: -- Summary: evaluate debugString only when log level is debug Key: SPARK-10527 URL: https://issues.apache.org/jira/browse/SPARK-10527 Project: Spark Issue Type:

[jira] [Created] (SPARK-10528) spark-shell throws java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable.

Aliaksei Belablotski created SPARK-10528: Summary: spark-shell throws java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Key: SPARK-10528 URL:

[jira] [Commented] (SPARK-10014) ML model broadcasts should be stored in private vars

[ https://issues.apache.org/jira/browse/SPARK-10014?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738017#comment-14738017 ] Joseph K. Bradley commented on SPARK-10014: --- Per discussion on

[jira] [Assigned] (SPARK-10527) evaluate debugString only when log level is debug

[ https://issues.apache.org/jira/browse/SPARK-10527?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10527: Assignee: Apache Spark > evaluate debugString only when log level is debug >

[jira] [Commented] (SPARK-10527) evaluate debugString only when log level is debug

[ https://issues.apache.org/jira/browse/SPARK-10527?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738041#comment-14738041 ] Apache Spark commented on SPARK-10527: -- User 'saucam' has created a pull request for this issue:

[jira] [Assigned] (SPARK-10527) evaluate debugString only when log level is debug

[ https://issues.apache.org/jira/browse/SPARK-10527?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Apache Spark reassigned SPARK-10527: Assignee: (was: Apache Spark) > evaluate debugString only when log level is debug >

[jira] [Commented] (SPARK-10528) spark-shell throws java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable.

[ https://issues.apache.org/jira/browse/SPARK-10528?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738074#comment-14738074 ] Marcelo Vanzin commented on SPARK-10528: Well, obvious question: what are the permissions of

[jira] [Commented] (SPARK-5556) Latent Dirichlet Allocation (LDA) using Gibbs sampler

[ https://issues.apache.org/jira/browse/SPARK-5556?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738090#comment-14738090 ] ding commented on SPARK-5556: - We have made the spark package and it can be find here

[jira] [Commented] (SPARK-10528) spark-shell throws java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable.

[ https://issues.apache.org/jira/browse/SPARK-10528?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738118#comment-14738118 ] Aliaksei Belablotski commented on SPARK-10528: -- Hi Marcelo, thanks for quick response. I'm

[jira] [Created] (SPARK-10529) When creating multiple HiveContext objects in one jvm, jdbc connections to metastore cann't be released and it may cause PermGen OutOfMemoryError.

ZhengYaofeng created SPARK-10529: Summary: When creating multiple HiveContext objects in one jvm, jdbc connections to metastore cann't be released and it may cause PermGen OutOfMemoryError. Key: SPARK-10529 URL:

[jira] [Commented] (SPARK-10487) MLlib model fitting causes DataFrame write to break with OutOfMemory exception

[ https://issues.apache.org/jira/browse/SPARK-10487?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738194#comment-14738194 ] Zoltan Toth commented on SPARK-10487: - Yes it only happens if you use mllib or ML and you fit a

[jira] [Comment Edited] (SPARK-10487) MLlib model fitting causes DataFrame write to break with OutOfMemory exception

[ https://issues.apache.org/jira/browse/SPARK-10487?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738194#comment-14738194 ] Zoltan Toth edited comment on SPARK-10487 at 9/10/15 5:28 AM: -- Yes it only

[jira] [Comment Edited] (SPARK-10487) MLlib model fitting causes DataFrame write to break with OutOfMemory exception

[ https://issues.apache.org/jira/browse/SPARK-10487?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14738194#comment-14738194 ] Zoltan Toth edited comment on SPARK-10487 at 9/10/15 5:29 AM: -- Yes it only

[jira] [Updated] (SPARK-10474) Aggregation failed with unable to acquire memory

[ https://issues.apache.org/jira/browse/SPARK-10474?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Davies Liu updated SPARK-10474: --- Target Version/s: 1.6.0, 1.5.1 Priority: Blocker (was: Critical) > Aggregation failed

[jira] [Created] (SPARK-10518) Update code examples in spark.ml user guide to use LIBSVM data source instead of MLUtils

Xiangrui Meng created SPARK-10518: - Summary: Update code examples in spark.ml user guide to use LIBSVM data source instead of MLUtils Key: SPARK-10518 URL: https://issues.apache.org/jira/browse/SPARK-10518

[jira] [Resolved] (SPARK-10461) make sure `input.primitive` is always variable name not code at GenerateUnsafeProjection

[ https://issues.apache.org/jira/browse/SPARK-10461?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Davies Liu resolved SPARK-10461. Resolution: Fixed Fix Version/s: 1.6.0 Issue resolved by pull request 8613

[jira] [Commented] (SPARK-10519) Investigate if we should encode timezone information to a timestamp value stored in JSON

[ https://issues.apache.org/jira/browse/SPARK-10519?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737375#comment-14737375 ] Davies Liu commented on SPARK-10519: +1 for 3, user have the ability to control timezone, it's also

[jira] [Commented] (SPARK-9924) checkForLogs and cleanLogs are scheduled at fixed rate and can get piled up

[ https://issues.apache.org/jira/browse/SPARK-9924?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737416#comment-14737416 ] Thomas Graves commented on SPARK-9924: -- [~vanzin] Any reason this wasn't picked back into spark 1.5

[jira] [Commented] (SPARK-10436) spark-submit overwrites spark.files defaults with the job script filename

[ https://issues.apache.org/jira/browse/SPARK-10436?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737544#comment-14737544 ] Sanket Reddy commented on SPARK-10436: -- I am a newbie and interested in it, I will take a look at

[jira] [Commented] (SPARK-7442) Spark 1.3.1 / Hadoop 2.6 prebuilt pacakge has broken S3 filesystem access

[ https://issues.apache.org/jira/browse/SPARK-7442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737580#comment-14737580 ] William Cox commented on SPARK-7442: Between this issue with the Hadoop 2.6 deploy and the bug with

[jira] [Commented] (SPARK-10493) reduceByKey not returning distinct results

[ https://issues.apache.org/jira/browse/SPARK-10493?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737252#comment-14737252 ] Sean Owen commented on SPARK-10493: --- What do you mean that it's not collapsing key pairs? the output of

[jira] [Comment Edited] (SPARK-10309) Some tasks failed with Unable to acquire memory

[ https://issues.apache.org/jira/browse/SPARK-10309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737185#comment-14737185 ] Davies Liu edited comment on SPARK-10309 at 9/9/15 4:53 PM: [~nadenf] Thanks

[jira] [Commented] (SPARK-10309) Some tasks failed with Unable to acquire memory

[ https://issues.apache.org/jira/browse/SPARK-10309?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737185#comment-14737185 ] Davies Liu commented on SPARK-10309: [~nadenf] Thanks for letting us know, just realized that your

[jira] [Commented] (SPARK-10495) For json data source, date values are saved as int strings

[ https://issues.apache.org/jira/browse/SPARK-10495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737161#comment-14737161 ] Yin Huai commented on SPARK-10495: -- Since we shipped Spark 1.5.0 with this issue, it will be good to

[jira] [Updated] (SPARK-10495) For json data source, date values are saved as int strings

[ https://issues.apache.org/jira/browse/SPARK-10495?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Yin Huai updated SPARK-10495: - Target Version/s: 1.6.0, 1.5.1 (was: 1.5.1) > For json data source, date values are saved as int

[jira] [Updated] (SPARK-10495) For json data source, date values are saved as int strings

[ https://issues.apache.org/jira/browse/SPARK-10495?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Yin Huai updated SPARK-10495: - Target Version/s: 1.5.1 Priority: Blocker (was: Critical) > For json data source, date

[jira] [Resolved] (SPARK-10481) SPARK_PREPEND_CLASSES make spark-yarn related jar could not be found

[ https://issues.apache.org/jira/browse/SPARK-10481?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Marcelo Vanzin resolved SPARK-10481. Resolution: Fixed Assignee: Jeff Zhang Fix Version/s: 1.6.0 >

[jira] [Commented] (SPARK-10493) reduceByKey not returning distinct results

[ https://issues.apache.org/jira/browse/SPARK-10493?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737296#comment-14737296 ] Glenn Strycker commented on SPARK-10493: [~srowen], the code I attached did run correctly.

[jira] [Commented] (SPARK-10519) Investigate if we should encode timezone information to a timestamp value stored in JSON

[ https://issues.apache.org/jira/browse/SPARK-10519?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737311#comment-14737311 ] Yin Huai commented on SPARK-10519: -- cc [~davies] I feel that option 3 is better. > Investigate if we

[jira] [Updated] (SPARK-10519) Investigate if we should encode timezone information to a timestamp value stored in JSON

[ https://issues.apache.org/jira/browse/SPARK-10519?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Yin Huai updated SPARK-10519: - Target Version/s: 1.6.0 > Investigate if we should encode timezone information to a timestamp value >

[jira] [Comment Edited] (SPARK-10495) For json data source, date values are saved as int strings

[ https://issues.apache.org/jira/browse/SPARK-10495?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14735964#comment-14735964 ] Yin Huai edited comment on SPARK-10495 at 9/9/15 4:40 PM: -- The bug itself is

[jira] [Created] (SPARK-10519) Investigate if we should encode timezone information to a timestamp value stored in JSON

Yin Huai created SPARK-10519: Summary: Investigate if we should encode timezone information to a timestamp value stored in JSON Key: SPARK-10519 URL: https://issues.apache.org/jira/browse/SPARK-10519

[jira] [Commented] (SPARK-10520) dates cannot be summarised in SparkR

[ https://issues.apache.org/jira/browse/SPARK-10520?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737486#comment-14737486 ] Shivaram Venkataraman commented on SPARK-10520: --- Thanks for the report -- I think this is a

[jira] [Updated] (SPARK-10520) dates cannot be summarised in SparkR

[ https://issues.apache.org/jira/browse/SPARK-10520?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Shivaram Venkataraman updated SPARK-10520: -- Component/s: SQL > dates cannot be summarised in SparkR >

[jira] [Updated] (SPARK-10520) dates cannot be summarised in SparkR

[ https://issues.apache.org/jira/browse/SPARK-10520?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-10520: Description: I create a simple dataframe in R and call the summary function on it (standard R,

[jira] [Updated] (SPARK-10520) dates cannot be summarised in SparkR

[ https://issues.apache.org/jira/browse/SPARK-10520?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Reynold Xin updated SPARK-10520: Description: I create a simple dataframe in R and call the summary function on it (standard R,

[jira] [Commented] (SPARK-10520) dates cannot be summarised in SparkR

[ https://issues.apache.org/jira/browse/SPARK-10520?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737520#comment-14737520 ] Vincent Warmerdam commented on SPARK-10520: --- Thought something similar, it seemed natural to

[jira] [Comment Edited] (SPARK-10520) dates cannot be summarised in SparkR

[ https://issues.apache.org/jira/browse/SPARK-10520?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737520#comment-14737520 ] Vincent Warmerdam edited comment on SPARK-10520 at 9/9/15 8:24 PM: --- I

[jira] [Commented] (SPARK-9924) checkForLogs and cleanLogs are scheduled at fixed rate and can get piled up

[ https://issues.apache.org/jira/browse/SPARK-9924?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737478#comment-14737478 ] Thomas Graves commented on SPARK-9924: -- Ok, thanks. wanted to make sure no known issues with pulling

[jira] [Created] (SPARK-10520) dates cannot be summarised in SparkR

Vincent Warmerdam created SPARK-10520: - Summary: dates cannot be summarised in SparkR Key: SPARK-10520 URL: https://issues.apache.org/jira/browse/SPARK-10520 Project: Spark Issue Type:

[jira] [Commented] (SPARK-9924) checkForLogs and cleanLogs are scheduled at fixed rate and can get piled up

[ https://issues.apache.org/jira/browse/SPARK-9924?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737452#comment-14737452 ] Marcelo Vanzin commented on SPARK-9924: --- Timing, I guess (it went in around code freeze time). We

[jira] [Commented] (SPARK-9503) Mesos dispatcher NullPointerException (MesosClusterScheduler)

[ https://issues.apache.org/jira/browse/SPARK-9503?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737453#comment-14737453 ] Timothy Chen commented on SPARK-9503: - Sorry this is indeed a bug and a fix is already in 1.5. Please

[jira] [Created] (SPARK-10521) Utilize Docker to test DB2 JDBC Dialect support

Luciano Resende created SPARK-10521: --- Summary: Utilize Docker to test DB2 JDBC Dialect support Key: SPARK-10521 URL: https://issues.apache.org/jira/browse/SPARK-10521 Project: Spark Issue

[jira] [Commented] (SPARK-1169) Add countApproxDistinctByKey to PySpark

[ https://issues.apache.org/jira/browse/SPARK-1169?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737608#comment-14737608 ] William Cox commented on SPARK-1169: I would like this feature. > Add countApproxDistinctByKey to

[jira] [Commented] (SPARK-10519) Investigate if we should encode timezone information to a timestamp value stored in JSON

[ https://issues.apache.org/jira/browse/SPARK-10519?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737612#comment-14737612 ] Sean Owen commented on SPARK-10519: --- I always feel nervous when storing human readable times without a

[jira] [Commented] (SPARK-10521) Utilize Docker to test DB2 JDBC Dialect support

[ https://issues.apache.org/jira/browse/SPARK-10521?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737635#comment-14737635 ] Luciano Resende commented on SPARK-10521: - I'll be submitting a PR for this shortly. > Utilize

[jira] [Commented] (SPARK-10439) Catalyst should check for overflow / underflow of date and timestamp values

[ https://issues.apache.org/jira/browse/SPARK-10439?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737644#comment-14737644 ] Davies Liu commented on SPARK-10439: There are many places there could be overflow, even for A + B,

[jira] [Commented] (SPARK-4036) Add Conditional Random Fields (CRF) algorithm to Spark MLlib

[ https://issues.apache.org/jira/browse/SPARK-4036?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel=14737650#comment-14737650 ] Xin Jin commented on SPARK-4036: Are we still actively working on this task? I have some work experience

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