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Vihang Karajgaonkar commented on HIVE-15879: -------------------------------------------- I agree that the patch does not improve the case of have 1 level of partition. It performs similar to existing approach. Did a simple test with single partitioned key table with ~1800 partitions on S3. Both the implementations take about the same time ~60 sec. But we quickly start seeing the benefits of this approach as soon as the number of partition keys increase. Repeated the test above with a 2 partition keys with 10*10 = 100 partitions. Results shown below show significant performance gain with the default configs. || Default pool size || Before || After || || Time taken (sec) | 19.8 | 3.27 | Hi [~rajesh.balamohan] I can change the JIRA description and category to "Improvement" if you think that is more appropriate. Thanks! Also updating the review board with patch HIVE-15879.03.patch > Fix HiveMetaStoreChecker.checkPartitionDirs method > -------------------------------------------------- > > Key: HIVE-15879 > URL: https://issues.apache.org/jira/browse/HIVE-15879 > Project: Hive > Issue Type: Bug > Reporter: Vihang Karajgaonkar > Assignee: Vihang Karajgaonkar > Attachments: HIVE-15879.01.patch, HIVE-15879.02.patch, > HIVE-15879.03.patch > > > HIVE-15803 fixes the msck hang issue in > HiveMetaStoreChecker.checkPartitionDirs method by adding a check to see if > the Threadpool has any spare threads. If not it uses single threaded listing > of the files. > {noformat} > if (pool != null) { > synchronized (pool) { > // In case of recursive calls, it is possible to deadlock with TP. > Check TP usage here. > if (pool.getActiveCount() < pool.getMaximumPoolSize()) { > useThreadPool = true; > } > if (!useThreadPool) { > if (LOG.isDebugEnabled()) { > LOG.debug("Not using threadPool as active count:" + > pool.getActiveCount() > + ", max:" + pool.getMaximumPoolSize()); > } > } > } > } > {noformat} > Based on the java doc of getActiveCount() below > bq. Returns the approximate number of threads that are actively executing > tasks. > it returns only approximate number of threads and it cannot be guaranteed > that it always returns the exact number of active threads. This still exposes > the method implementation to the msck hang bug in rare corner cases. > We could either: > 1. Use a atomic counter to track exactly how many threads are actively running > 2. Relook at the method itself to make it much simpler. Like eg, look into > the possibility of changing the recursive implementation to an iterative > implementation where worker threads pick tasks from a queue until the queue > is empty. -- This message was sent by Atlassian JIRA (v6.3.15#6346)