Hbase is helpful modeling dynamic properties because of flexible data model. Hbase s columns are split up into column families these are logical groupings of columns. Hive allows you to issue queries against petabytes of data, using its hive query language hql which is similar to sql. While hbase does have tables, rows, and columns there are some powerful differences. Hbase architecture in hbase, tables are split into regions and are served by the region servers. I particularly liked the tables giving the meaning of the various import and export features of sqoop.
When a region grows too large, it splits into two child regions. This will divide the region s load over multiple region servers. It is hard to trace the logs to understand region level problems if it keeps splitting and getting renamed. The chapter ends with a look at metadata, describing what metadata is, and why its important. The chapter has an indepth look at sqoops data transfer capabilities. For most use patterns, most of the time, you should use automatic splitting. Important considerations for choosing the row key are discussed. We split the table into 210 regions in 1 tb dataset cases to avoid region split at runtime. Hbase is a realtime columnoriented database that runs on top of hadoop. Regions are vertically divided by column families into. Its only recommended when we know the distribution of the keys, else presplitting might run into uneven. Splitting hbase tables, examples and best practices. Tables are split into chunks of rows called regions.
The only way to alleviate the situation is to manually split a hot region into one or more new regions, at exact boundaries. Hbase tables can have millions of columns and billions of rows. Instead of allowing hbase to split your regions automatically, you can choose to manage the splitting yourself. A region is decided to be split when store file size goes above hbase. Hbase presplitting and maximum region size stack overflow. In hbase, the equivalent of a volume is called a region. Apache hbase distributes its load through region splitting. Oozie is a workflow and scheduler system for hadoop jobs. A simplistic view of splitting is that when a region grows to hbase.