Is the replication enabled and setup properly? Are you creating snapshots or is backup enabled (hbase.backup.enable) ?
Check under ../hbase folder whats actually taking more space. On Wed, 30 Jan 2019 at 6:24 AM, talluri abhishek <abhishektall...@gmail.com> wrote: > Hi Vincent, > > Versions is set to1 and keep_deleted_cells is false. It's basically the > default settings and nothing has been changed. > > describe on the hbase table gives below: > > VERSIONS => '1', MIN_VERSIONS => '0', TTL => 'FOREVER', KEEP_DELETED_CELLS => > 'FALSE' > > > Thanks, > Abhishek > > On Tue, Jan 29, 2019 at 3:20 PM Vincent Poon <vincentp...@apache.org> > wrote: > >> is your max_versions set to 1 ? keep_deleted_cells? >> >> On Tue, Jan 29, 2019 at 10:41 AM talluri abhishek < >> abhishektall...@gmail.com> wrote: >> >>> Hi All, >>> >>> We are seeing a couple of issues on some of our Phoenix tables where the >>> size of the tables keep growing 2-3 times after around 2-3 days of >>> ingestion and the read performance takes a big hit after that. Now, if we >>> insert overwrite the data in that table to a new copy table, the data size >>> comes back to normal size and the queries perform fast on that copy table. >>> >>> Initial table size after 1st day ~ 5G >>> After 2 days of ingestion ~ 15G >>> Re-write into a copy table ~ 5-6 G >>> >>> Query performance becomes proportional to the size of the table, lets >>> say the query took 40 secs to run on the original table after first day, it >>> takes around 130-160 secs after 2 days of ingestion. The same query when >>> run on the copy table finishes in around ~40secs. >>> >>> Most of the ingested data after the first day are mostly updates >>> happening on the existing rows, so we thought major compaction should solve >>> the size issue but it does not shrink the size every time (load happens in >>> parallel when the compaction is run). >>> Write performance is always good and we have used salt buckets to even >>> out the writes. The primary key is a 12-bit string which is made by the >>> concatenation of some account id and an auto-generated transaction number. >>> >>> One query that has a toll on its performance as mentioned above is: >>> *select (list of 50-70 columns) from original_table where account_id IN >>> (list of 100k account ids) *[account_id in this query is the primary >>> key on that table] >>> >>> We are currently increasing the heap space on these region servers to >>> provide more memstore size, which could reduce the number of flushes >>> for the upserted data. >>> >>> Could there be any other reason for the increase in the size of the >>> table apart from the updated rows? How could we better the performance of >>> those read queries? >>> >>> Thanks, >>> Abhishek >>> >>
