[jira] [Commented] (SPARK-9539) Repeated sc.close() in PySpark causes JVM memory leak
[ https://issues.apache.org/jira/browse/SPARK-9539?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14651067#comment-14651067 ] Andrey Zimovnov commented on SPARK-9539: Hi, Owen! I'm not sure what Permanent in java heap means, but it grows with time. I really have such a use case, when I need to recreate spark context a lot. The only workaround for now is to try to increase MaxPermSize, I guess. Repeated sc.close() in PySpark causes JVM memory leak - Key: SPARK-9539 URL: https://issues.apache.org/jira/browse/SPARK-9539 Project: Spark Issue Type: Bug Components: PySpark Affects Versions: 1.4.1 Reporter: Andrey Zimovnov Priority: Minor Attachments: Screenshot at авг. 02 19-10-53.png Example code in Python: {code:python} for i in range(20): print i conf = SparkConf().setAppName(test) sc = SparkContext(conf=conf) hivec = HiveContext(sc) hivec.sql(select id from details_info limit 1).show() sc.stop() del hivec del sc {code} Jstat output: {noformat} S0CS1CS0US1U EC EUOC OU PC PUYGC YGCTFGCFGCT GCT 196608,0 196608,0 97566,2 0,0 1179648,0 542150,0 3145728,0120,0 154112,0 153613,2 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 679041,7 3145728,0120,0 164352,0 164183,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 907928,4 3145728,0120,0 164352,0 164200,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 912132,7 3145728,0120,0 164352,0 164200,5 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 913741,5 3145728,0120,0 164352,0 164200,8 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 929458,6 3145728,0120,0 164352,0 164206,0 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 1003138,1 3145728,0120,0 168960,0 168646,0 40,434 0 0,0000,434 131584,0 196608,0 0,0 109725,6 1179648,0 0,03145728,0128,0 175104,0 174802,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 152654,9 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 158586,1 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 160659,8 3145728,0128,0 175104,0 174805,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 181935,2 3145728,0128,0 175104,0 174819,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 283389,1 3145728,0128,0 185856,0 185371,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 342596,4 3145728,0128,0 185856,0 185379,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 547634,7 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 555930,9 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 557888,6 3145728,0128,0 185856,0 185386,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 573907,5 3145728,0128,0 185856,0 185397,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 637955,0 3145728,0128,0 189952,0 189533,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 895866,1 3145728,0128,0 196096,0 195968,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 948046,5 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 952427,2 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 957977,5 3145728,0128,0 196096,0 195973,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 977811,1 3145728,0128,0 196096,0 195977,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 1118722,0 3145728,0128,0 206848,0 206539,0 50,591 0 0,0000,591 131584,0 144384,0 118692,5 0,0 1284096,0 183470,8 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 189718,5 3145728,0136,0
[jira] [Updated] (SPARK-9539) Repeated sc.close() in PySpark causes JVM memory leak
[ https://issues.apache.org/jira/browse/SPARK-9539?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Andrey Zimovnov updated SPARK-9539: --- Description: Example code in Python: {code:python} for i in range(20): print i conf = SparkConf().setAppName(test) sc = SparkContext(conf=conf) hivec = HiveContext(sc) hivec.sql(select id from details_info limit 1).show() sc.stop() del hivec del sc {code} Jstat output: {noformat} S0CS1CS0US1U EC EUOC OU PC PU YGC YGCTFGCFGCT GCT 196608,0 196608,0 97566,2 0,0 1179648,0 542150,0 3145728,0120,0 154112,0 153613,2 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 679041,7 3145728,0120,0 164352,0 164183,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 907928,4 3145728,0120,0 164352,0 164200,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 912132,7 3145728,0120,0 164352,0 164200,5 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 913741,5 3145728,0120,0 164352,0 164200,8 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 929458,6 3145728,0120,0 164352,0 164206,0 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 1003138,1 3145728,0120,0 168960,0 168646,0 40,434 0 0,0000,434 131584,0 196608,0 0,0 109725,6 1179648,0 0,03145728,0128,0 175104,0 174802,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 152654,9 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 158586,1 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 160659,8 3145728,0128,0 175104,0 174805,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 181935,2 3145728,0128,0 175104,0 174819,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 283389,1 3145728,0128,0 185856,0 185371,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 342596,4 3145728,0128,0 185856,0 185379,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 547634,7 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 555930,9 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 557888,6 3145728,0128,0 185856,0 185386,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 573907,5 3145728,0128,0 185856,0 185397,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 637955,0 3145728,0128,0 189952,0 189533,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 895866,1 3145728,0128,0 196096,0 195968,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 948046,5 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 952427,2 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 957977,5 3145728,0128,0 196096,0 195973,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 977811,1 3145728,0128,0 196096,0 195977,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 1118722,0 3145728,0128,0 206848,0 206539,0 50,591 0 0,0000,591 131584,0 144384,0 118692,5 0,0 1284096,0 183470,8 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 189718,5 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 192165,0 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 199848,4 3145728,0136,0 206848,0 206546,9 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 219687,6 3145728,0136,0 206848,0 206552,2 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 358272,4 3145728,0136,0 217600,0 217100,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 573543,6 3145728,0136,0 217600,0 217109,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0
[jira] [Updated] (SPARK-9539) Repeated sc.close() in PySpark causes JVM memory leak
[ https://issues.apache.org/jira/browse/SPARK-9539?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Andrey Zimovnov updated SPARK-9539: --- Attachment: Screenshot at авг. 02 19-10-53.png jstat visualization Repeated sc.close() in PySpark causes JVM memory leak - Key: SPARK-9539 URL: https://issues.apache.org/jira/browse/SPARK-9539 Project: Spark Issue Type: Bug Components: PySpark Affects Versions: 1.4.1 Reporter: Andrey Zimovnov Priority: Minor Attachments: Screenshot at авг. 02 19-10-53.png Example code in Python: {code:python} for i in range(20): print i conf = SparkConf().setAppName(test) sc = SparkContext(conf=conf) hivec = HiveContext(sc) hivec.sql(select id from details_info limit 1).show() sc.stop() del hivec del sc {code} Jstat output: {noformat} S0CS1CS0US1U EC EUOC OU PC PUYGC YGCTFGCFGCT GCT 196608,0 196608,0 97566,2 0,0 1179648,0 542150,0 3145728,0120,0 154112,0 153613,2 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 679041,7 3145728,0120,0 164352,0 164183,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 907928,4 3145728,0120,0 164352,0 164200,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 912132,7 3145728,0120,0 164352,0 164200,5 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 913741,5 3145728,0120,0 164352,0 164200,8 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 929458,6 3145728,0120,0 164352,0 164206,0 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 1003138,1 3145728,0120,0 168960,0 168646,0 40,434 0 0,0000,434 131584,0 196608,0 0,0 109725,6 1179648,0 0,03145728,0128,0 175104,0 174802,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 152654,9 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 158586,1 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 160659,8 3145728,0128,0 175104,0 174805,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 181935,2 3145728,0128,0 175104,0 174819,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 283389,1 3145728,0128,0 185856,0 185371,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 342596,4 3145728,0128,0 185856,0 185379,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 547634,7 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 555930,9 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 557888,6 3145728,0128,0 185856,0 185386,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 573907,5 3145728,0128,0 185856,0 185397,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 637955,0 3145728,0128,0 189952,0 189533,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 895866,1 3145728,0128,0 196096,0 195968,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 948046,5 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 952427,2 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 957977,5 3145728,0128,0 196096,0 195973,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 977811,1 3145728,0128,0 196096,0 195977,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 1118722,0 3145728,0128,0 206848,0 206539,0 50,591 0 0,0000,591 131584,0 144384,0 118692,5 0,0 1284096,0 183470,8 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 189718,5 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 192165,0 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0
[jira] [Commented] (SPARK-9539) Repeated sc.close() in PySpark causes JVM memory leak
[ https://issues.apache.org/jira/browse/SPARK-9539?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanelfocusedCommentId=14651078#comment-14651078 ] Andrey Zimovnov commented on SPARK-9539: OK, I'll work on this later and reopen if necessary. Thanks! Repeated sc.close() in PySpark causes JVM memory leak - Key: SPARK-9539 URL: https://issues.apache.org/jira/browse/SPARK-9539 Project: Spark Issue Type: Bug Components: PySpark Affects Versions: 1.4.1 Reporter: Andrey Zimovnov Priority: Minor Attachments: Screenshot at авг. 02 19-10-53.png Example code in Python: {code:python} for i in range(20): print i conf = SparkConf().setAppName(test) sc = SparkContext(conf=conf) hivec = HiveContext(sc) hivec.sql(select id from details_info limit 1).show() sc.stop() del hivec del sc {code} Jstat output: {noformat} S0CS1CS0US1U EC EUOC OU PC PUYGC YGCTFGCFGCT GCT 196608,0 196608,0 97566,2 0,0 1179648,0 542150,0 3145728,0120,0 154112,0 153613,2 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 679041,7 3145728,0120,0 164352,0 164183,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 907928,4 3145728,0120,0 164352,0 164200,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 912132,7 3145728,0120,0 164352,0 164200,5 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 913741,5 3145728,0120,0 164352,0 164200,8 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 929458,6 3145728,0120,0 164352,0 164206,0 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 1003138,1 3145728,0120,0 168960,0 168646,0 40,434 0 0,0000,434 131584,0 196608,0 0,0 109725,6 1179648,0 0,03145728,0128,0 175104,0 174802,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 152654,9 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 158586,1 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 160659,8 3145728,0128,0 175104,0 174805,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 181935,2 3145728,0128,0 175104,0 174819,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 283389,1 3145728,0128,0 185856,0 185371,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 342596,4 3145728,0128,0 185856,0 185379,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 547634,7 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 555930,9 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 557888,6 3145728,0128,0 185856,0 185386,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 573907,5 3145728,0128,0 185856,0 185397,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 637955,0 3145728,0128,0 189952,0 189533,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 895866,1 3145728,0128,0 196096,0 195968,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 948046,5 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 952427,2 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 957977,5 3145728,0128,0 196096,0 195973,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 977811,1 3145728,0128,0 196096,0 195977,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 1118722,0 3145728,0128,0 206848,0 206539,0 50,591 0 0,0000,591 131584,0 144384,0 118692,5 0,0 1284096,0 183470,8 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 189718,5 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 192165,0 3145728,0136,0 206848,0 206543,4 6
[jira] [Created] (SPARK-9539) Repeated sc.close() in PySpark causes JVM memory leak
Andrey Zimovnov created SPARK-9539: -- Summary: Repeated sc.close() in PySpark causes JVM memory leak Key: SPARK-9539 URL: https://issues.apache.org/jira/browse/SPARK-9539 Project: Spark Issue Type: Bug Components: PySpark Affects Versions: 1.4.1 Reporter: Andrey Zimovnov Priority: Minor Example code in Python: for i in range(20): print i conf = SparkConf().setAppName(test) sc = SparkContext(conf=conf) hivec = HiveContext(sc) hivec.sql(select id from details_info limit 1).show() sc.stop() del hivec del sc Jstat output: S0CS1CS0US1U EC EUOC OU PC PU YGC YGCTFGCFGCT GCT 196608,0 196608,0 97566,2 0,0 1179648,0 542150,0 3145728,0120,0 154112,0 153613,2 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 679041,7 3145728,0120,0 164352,0 164183,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 907928,4 3145728,0120,0 164352,0 164200,3 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 912132,7 3145728,0120,0 164352,0 164200,5 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 913741,5 3145728,0120,0 164352,0 164200,8 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 929458,6 3145728,0120,0 164352,0 164206,0 40,434 0 0,0000,434 196608,0 196608,0 97566,2 0,0 1179648,0 1003138,1 3145728,0120,0 168960,0 168646,0 40,434 0 0,0000,434 131584,0 196608,0 0,0 109725,6 1179648,0 0,03145728,0128,0 175104,0 174802,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 152654,9 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 158586,1 3145728,0128,0 175104,0 174803,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 160659,8 3145728,0128,0 175104,0 174805,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 181935,2 3145728,0128,0 175104,0 174819,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 283389,1 3145728,0128,0 185856,0 185371,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 342596,4 3145728,0128,0 185856,0 185379,3 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 547634,7 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 555930,9 3145728,0128,0 185856,0 185385,8 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 557888,6 3145728,0128,0 185856,0 185386,0 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 573907,5 3145728,0128,0 185856,0 185397,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 637955,0 3145728,0128,0 189952,0 189533,1 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 895866,1 3145728,0128,0 196096,0 195968,5 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 948046,5 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 952427,2 3145728,0128,0 196096,0 195969,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 957977,5 3145728,0128,0 196096,0 195973,4 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 977811,1 3145728,0128,0 196096,0 195977,7 50,591 0 0,0000,591 131584,0 196608,0 0,0 109725,6 1179648,0 1118722,0 3145728,0128,0 206848,0 206539,0 50,591 0 0,0000,591 131584,0 144384,0 118692,5 0,0 1284096,0 183470,8 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 189718,5 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 192165,0 3145728,0136,0 206848,0 206543,4 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 199848,4 3145728,0136,0 206848,0 206546,9 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 219687,6 3145728,0136,0 206848,0 206552,2 60,773 0 0,0000,773 131584,0 144384,0 118692,5 0,0 1284096,0 358272,4 3145728,0136,0 217600,0 217100,4 60,773 0 0,000
[jira] [Updated] (SPARK-5271) PySpark History Web UI issues
[ https://issues.apache.org/jira/browse/SPARK-5271?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Andrey Zimovnov updated SPARK-5271: --- Component/s: Web UI PySpark History Web UI issues - Key: SPARK-5271 URL: https://issues.apache.org/jira/browse/SPARK-5271 Project: Spark Issue Type: Bug Components: Web UI Affects Versions: 1.2.0 Environment: PySpark 1.2.0 in yarn-client mode Reporter: Andrey Zimovnov After successful run of PySpark app via spark-submit in yarn-client mode on Hadoop 2.4 cluster the History UI shows the same as in issue SPARK-3898. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Created] (SPARK-5271) PySpark History Web UI issues
Andrey Zimovnov created SPARK-5271: -- Summary: PySpark History Web UI issues Key: SPARK-5271 URL: https://issues.apache.org/jira/browse/SPARK-5271 Project: Spark Issue Type: Bug Affects Versions: 1.2.0 Environment: PySpark 1.2.0 in yarn-client mode Reporter: Andrey Zimovnov After successful run of PySpark app via spark-submit in yarn-client mode on Hadoop 2.4 cluster the History UI shows the same as in issue SPARK-3898. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org