![]() ![]() When number of sorted runs is small, Paimon writers will perform compaction asynchronously in separated threads, so records can be continuously written into the table. This is a trade-off between writing and query performance. ![]() However, if this value becomes too large, more memory and CPU time will be needed when querying the table. Includes level0 files (one file one sorted run) and high-level runs (one level one sorted run).Ĭompaction will become less frequent when paction-trigger becomes larger, thus improving writing performance. The sorted run number to trigger compaction. The following table property determines the minimum number of sorted runs to trigger a compaction. To keep the number of sorted runs in a reasonable range, Paimon writers will automatically perform compactions. One can easily see that too many sorted runs will result in poor query performance. When querying records from an LSM tree, all sorted runs must be combined to produce a complete view of all records. LSM organizes files in several sorted runs. Paimon uses LSM tree which supports a large number of updates. Number of Sorted Runs to Trigger Compaction By default, the parallelism is determined by the framework using the same parallelism of the upstream chained operator. Optionĭefines the parallelism of the sink operator. You can control the parallelism of the sink with the sink.parallelism table property. It is recommended that the parallelism of sink should be less than or equal to the number of buckets, preferably equal. Performance of Paimon writers are related with the following factors. We recommend you use the latest stable version. This documentation is for an unreleased version of Apache Paimon. Number of Sorted Runs to Trigger Compaction. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |