[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2018-01-30 Thread Xiao Li (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiao Li updated SPARK-20392: Component/s: SQL > Slow performance when calling fit on ML pipeline for dataset with many > columns but fe

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-12-05 Thread Xiao Li (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiao Li updated SPARK-20392: Priority: Major (was: Blocker) > Slow performance when calling fit on ML pipeline for dataset with many >

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-05-30 Thread Wenchen Fan (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Wenchen Fan updated SPARK-20392: Target Version/s: 2.3.0 > Slow performance when calling fit on ML pipeline for dataset with many >

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-05-30 Thread Wenchen Fan (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Wenchen Fan updated SPARK-20392: Priority: Blocker (was: Major) > Slow performance when calling fit on ML pipeline for dataset with

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-05-30 Thread Wenchen Fan (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Wenchen Fan updated SPARK-20392: Issue Type: Improvement (was: Bug) > Slow performance when calling fit on ML pipeline for dataset

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-05-30 Thread Wenchen Fan (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Wenchen Fan updated SPARK-20392: Fix Version/s: (was: 2.3.0) > Slow performance when calling fit on ML pipeline for dataset with

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-04-24 Thread Barry Becker (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Barry Becker updated SPARK-20392: - Attachment: model_9756.zip blockbuster_fewCols.csv attaching blockbuster_fewCols.

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-04-21 Thread Barry Becker (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Barry Becker updated SPARK-20392: - Attachment: model_9754.zip Attaching the parquet pipeline (as zip). > Slow performance when call

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-04-19 Thread Barry Becker (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Barry Becker updated SPARK-20392: - Attachment: giant_query_plan_for_fitting_pipeline.txt Giant nested query plan using when calling

[jira] [Updated] (SPARK-20392) Slow performance when calling fit on ML pipeline for dataset with many columns but few rows

2017-04-19 Thread Barry Becker (JIRA)
[ https://issues.apache.org/jira/browse/SPARK-20392?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Barry Becker updated SPARK-20392: - Attachment: blockbuster.csv Attaching blockbuster.csv data file with many columns, but few rows.