Get the App
SLTechnology News&Howtos  ›  Servers  › 

What are Compact and Split in HBase

Shulou Source: shulou.com Published: 2022-05-31 21:23:35 10月24日 Update

This article is about what Compact and Split are in HBase. The editor thinks it is very practical, so share it with you as a reference and follow the editor to have a look.

Compact

HStore storage is the core of HBase storage, which consists of two parts, one is MemStore and the other is StoreFiles.

MemStore is Sorted Memory Buffer, and the data written by the user will first be put into MemStore. When the MemStore is full, it will be Flush into a StoreFile (the underlying implementation is HFile). When the number of StoreFile files increases to a certain threshold, Compact merge operation will be triggered, multiple StoreFiles will be merged into one StoreFile, and version merging and data deletion will be carried out in the merge process.

Therefore, we can see that HBase can only add data, and all updates and deletions are carried out in the subsequent compact process.

This enables the user's write operations to be returned as soon as they enter the memory, ensuring the high performance of HBase Imax O.

Split

After StoreFiles Compact, larger and larger StoreFile will be formed gradually, and when the size of a single StoreFile exceeds a certain threshold, it will

Trigger the Split operation, and change the current Region Split to 2 Region, the parent Region will be offline, and the 2 children from the new Split will be Region.

Will be assigned by the HMaster to the corresponding HRegionServer, so that the pressure of the original 1 Region can be diverted to 2 Region.

The following figure describes the process of Compaction and Split:

Thank you for reading! This is the end of the article on "what are Compact and Split in HBase". I hope the above content can be of some help to you, so that you can learn more knowledge. if you think the article is good, you can share it for more people to see!

Tags: Data process content more users articles thresholds storage good practical below offline memory single pressure only multiple size kids Apple Docker Huawei Linux macOS MariaDB Microsoft MySQL NVidia OPPO Reno NVidia Shulou Tech Info Redmi Microsoft Apple