Repository: carbondata Updated Branches: refs/heads/master 7dea46168 -> 4a090ce27
[CARBONDATA-3007][Doc] Fix error in documents This closes #2813 Project: http://git-wip-us.apache.org/repos/asf/carbondata/repo Commit: http://git-wip-us.apache.org/repos/asf/carbondata/commit/4a090ce2 Tree: http://git-wip-us.apache.org/repos/asf/carbondata/tree/4a090ce2 Diff: http://git-wip-us.apache.org/repos/asf/carbondata/diff/4a090ce2 Branch: refs/heads/master Commit: 4a090ce27ee7d42bc76de812f300d3d72976eb18 Parents: 7dea461 Author: xuchuanyin <[email protected]> Authored: Mon Oct 15 20:23:22 2018 +0800 Committer: Jacky Li <[email protected]> Committed: Thu Oct 18 17:05:56 2018 +0800 ---------------------------------------------------------------------- docs/performance-tuning.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/carbondata/blob/4a090ce2/docs/performance-tuning.md ---------------------------------------------------------------------- diff --git a/docs/performance-tuning.md b/docs/performance-tuning.md index 6c87ce9..f43385a 100644 --- a/docs/performance-tuning.md +++ b/docs/performance-tuning.md @@ -168,7 +168,7 @@ | carbon.compaction.level.threshold | spark/carbonlib/carbon.properties | Data loading and Querying | For minor compaction, specifies the number of segments to be merged in stage 1 and number of compacted segments to be merged in stage 2. | Each CarbonData load will create one segment, if every load is small in size it will generate many small files over a period of time impacting the query performance. Configuring this parameter will merge the small segment to one big segment which will sort the data and improve the performance. For Example in one telecommunication scenario, the performance improves about 2 times after minor compaction. | | spark.sql.shuffle.partitions | spark/conf/spark-defaults.conf | Querying | The number of task started when spark shuffle. | The value can be 1 to 2 times as much as the executor cores. In an aggregation scenario, reducing the number from 200 to 32 reduced the query time from 17 to 9 seconds. | | spark.executor.instances/spark.executor.cores/spark.executor.memory | spark/conf/spark-defaults.conf | Querying | The number of executors, CPU cores, and memory used for CarbonData query. | In the bank scenario, we provide the 4 CPUs cores and 15 GB for each executor which can get good performance. This 2 value does not mean more the better. It needs to be configured properly in case of limited resources. For example, In the bank scenario, it has enough CPU 32 cores each node but less memory 64 GB each node. So we cannot give more CPU but less memory. For example, when 4 cores and 12GB for each executor. It sometimes happens GC during the query which impact the query performance very much from the 3 second to more than 15 seconds. In this scenario need to increase the memory or decrease the CPU cores. | -| carbon.detail.batch.size | spark/carbonlib/carbon.properties | Data loading | The buffer size to store records, returned from the block scan. | In limit scenario this parameter is very important. For example your query limit is 1000. But if we set this value to 3000 that means we get 3000 records from scan but spark will only take 1000 rows. So the 2000 remaining are useless. In one Finance test case after we set it to 100, in the limit 1000 scenario the performance increase about 2 times in comparison to if we set this value to 12000. | +| carbon.detail.batch.size | spark/carbonlib/carbon.properties | Querying | The buffer size to store records, returned from the block scan. | In limit scenario this parameter is very important. For example your query limit is 1000. But if we set this value to 3000 that means we get 3000 records from scan but spark will only take 1000 rows. So the 2000 remaining are useless. In one Finance test case after we set it to 100, in the limit 1000 scenario the performance increase about 2 times in comparison to if we set this value to 12000. | | carbon.use.local.dir | spark/carbonlib/carbon.properties | Data loading | Whether use YARN local directories for multi-table load disk load balance | If this is set it to true CarbonData will use YARN local directories for multi-table load disk load balance, that will improve the data load performance. | | carbon.use.multiple.temp.dir | spark/carbonlib/carbon.properties | Data loading | Whether to use multiple YARN local directories during table data loading for disk load balance | After enabling 'carbon.use.local.dir', if this is set to true, CarbonData will use all YARN local directories during data load for disk load balance, that will improve the data load performance. Please enable this property when you encounter disk hotspot problem during data loading. | | carbon.sort.temp.compressor | spark/carbonlib/carbon.properties | Data loading | Specify the name of compressor to compress the intermediate sort temporary files during sort procedure in data loading. | The optional values are 'SNAPPY','GZIP','BZIP2','LZ4','ZSTD', and empty. By default, empty means that Carbondata will not compress the sort temp files. This parameter will be useful if you encounter disk bottleneck. |
