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Posted to issues-all@impala.apache.org by "Quanlong Huang (Jira)" <ji...@apache.org> on 2023/01/02 07:42:00 UTC
[jira] [Updated] (IMPALA-11812) Catalogd OOM due to lots of HMS FieldSchema instances
[ https://issues.apache.org/jira/browse/IMPALA-11812?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Quanlong Huang updated IMPALA-11812:
------------------------------------
Target Version: Impala 4.1.1
> Catalogd OOM due to lots of HMS FieldSchema instances
> -----------------------------------------------------
>
> Key: IMPALA-11812
> URL: https://issues.apache.org/jira/browse/IMPALA-11812
> Project: IMPALA
> Issue Type: Bug
> Components: Catalog
> Reporter: Quanlong Huang
> Assignee: Quanlong Huang
> Priority: Critical
> Fix For: Impala 4.3.0
>
> Attachments: MAT_dominator_tree.png, create_ext_tbl_with_5k_cols_50k_parts.sh, wide-table-loading-oom-FieldSchema-path2root.png, wide-table-loading-oom-histogram.png, wide-table-loading-oom-top-consumers.png
>
>
> For partitioned wide tables that have thousands of columns, catalogd might hit OOM in routines on them. E.g. when running AlterTableRecoverPartitions for all their partitions, or when initially loading all partitions of them.
> The direct reason is that the heap is full of HMS FieldSchema instances. Here is a histogram of the issue in a 4GB heap:
> {noformat}
> Class Name | Objects | Shallow Heap |
> --------------------------------------------------------------------------------------------
> org.apache.hadoop.hive.metastore.api.FieldSchema | 111,876,486 | 2,685,035,664 |
> java.lang.Object[] | 78,026 | 449,929,656 |
> char[] | 91,295 | 6,241,744 |
> java.util.ArrayList | 171,126 | 4,107,024 |
> java.util.HashMap | 71,135 | 3,414,480 |
> java.lang.String | 91,161 | 2,187,864 |
> java.util.concurrent.ConcurrentHashMap$Node | 59,614 | 1,907,648 |
> java.util.concurrent.atomic.LongAdder | 53,021 | 1,696,672 |
> org.apache.hadoop.hive.metastore.api.Partition | 22,374 | 1,610,928 |
> com.codahale.metrics.EWMA | 30,780 | 1,477,440 |
> com.codahale.metrics.LongAdderProxy$JdkProvider$1 | 53,021 | 1,272,504 |
> org.apache.hadoop.hive.metastore.api.StorageDescriptor | 22,376 | 1,253,056 |
> java.util.Hashtable$Entry | 36,921 | 1,181,472 |
> java.util.concurrent.atomic.AtomicLong | 39,444 | 946,656 |
> org.apache.hadoop.hive.metastore.api.SerDeInfo | 22,375 | 895,000 |
> byte[] | 1,686 | 668,480 |
> java.util.concurrent.ConcurrentHashMap$Node[] | 1,874 | 639,824 |
> com.codahale.metrics.ExponentiallyDecayingReservoir | 10,259 | 574,504 |
> java.util.HashMap$Node | 17,776 | 568,832 |
> org.apache.hadoop.hive.metastore.api.SkewedInfo | 22,375 | 537,000 |
> com.codahale.metrics.Meter | 10,260 | 492,480 |
> java.util.concurrent.ConcurrentSkipListMap | 10,260 | 492,480 |
> java.util.concurrent.locks.ReentrantReadWriteLock$NonfairSync| 10,259 | 492,432 |
> org.apache.impala.catalog.ColumnStats | 5,003 | 400,240 |
> Total: 24 of 6,158 entries; 6,130 more | 113,007,927 | 3,174,330,288 | {noformat}
> In the above case, these FieldSchema instances come from the list of hmsPartitions that is created locally by CatalogOpExecutor#alterTableRecoverPartitions(). The thread is 0x6d051abb8:
> !MAT_dominator_tree.png|width=825,height=308!
> Stacktrace:
> {noformat}
> Thread 0x6d051abb8
> at org.apache.hadoop.hive.metastore.api.StorageDescriptor.<init>(Lorg/apache/hadoop/hive/metastore/api/StorageDescriptor;)V (StorageDescriptor.java:216)
> at org.apache.hadoop.hive.metastore.api.StorageDescriptor.deepCopy()Lorg/apache/hadoop/hive/metastore/api/StorageDescriptor; (StorageDescriptor.java:256)
> at org.apache.impala.service.CatalogOpExecutor.createHmsPartitionFromValues(Ljava/util/List;Lorg/apache/hadoop/hive/metastore/api/Table;Lorg/apache/impala/analysis/TableName;Ljava/lang/String;)Lorg/apache/hadoop/hive/metastore/api/Partition; (CatalogOpExecutor.java:5787)
> at org.apache.impala.service.CatalogOpExecutor.alterTableRecoverPartitions(Lorg/apache/impala/catalog/Table;Ljava/lang/String;)V (CatalogOpExecutor.java:5678)
> at org.apache.impala.service.CatalogOpExecutor.alterTable(Lorg/apache/impala/thrift/TAlterTableParams;Ljava/lang/String;ZLorg/apache/impala/thrift/TDdlExecResponse;)V (CatalogOpExecutor.java:1208)
> at org.apache.impala.service.CatalogOpExecutor.execDdlRequest(Lorg/apache/impala/thrift/TDdlExecRequest;)Lorg/apache/impala/thrift/TDdlExecResponse; (CatalogOpExecutor.java:419)
> at org.apache.impala.service.JniCatalog.execDdl([B)[B (JniCatalog.java:260){noformat}
> *How this happen*
> When creating the list of hmsPartitions, we deep copy the StorageDescriptor which will also deep copy the column list:
> {code:java}
> alterTableRecoverPartitions()
> -> createHmsPartitionFromValues()
> -> StorageDescriptor sd = msTbl.getSd().deepCopy();{code}
> Impala doesn't respect the partition level schema (by design), we should share the list of FieldSchema across hmsPartitions.
> When loading partition metadata for such a table, we could also hit this issue. The HMS API "get_partitions_by_names" returns the list of hmsPartitions. Each of them reference a unique list of FieldSchemas. We should deduplicate them to share the same column list. FWIW, attached the heap analysis results for wide table loading OOM (4GB heap):
> !wide-table-loading-oom-histogram.png|width=623,height=695!
> !wide-table-loading-oom-top-consumers.png|width=1066,height=434!
> The FieldSchema instances come from the metadata loading thread:
> !wide-table-loading-oom-FieldSchema-path2root.png|width=1023,height=213!
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