If you know your key space then you can use *SPLIT ON* in your table create DDL. See http://phoenix.apache.org/language
On Tue, Feb 2, 2016 at 11:54 AM, Serega Sheypak <[email protected]> wrote: > Hm... and what is the right to presplit table then? > > 2016-02-02 18:30 GMT+01:00 Mujtaba Chohan <[email protected]>: > >> If your filter matches few rows due to filter on leading part of PK then >> your data might only reside in a single block which leads to less >> overall disk reads for non-salted case vs need for multiple blocks reads for >> salted one. >> >> >> On Tuesday, February 2, 2016, Serega Sheypak <[email protected]> >> wrote: >> >>> > then you would be better off not using salt buckets all together >>> rather than having 100 parallel scan and block reads in your case. I >>> Didn't understand you correctly. What is difference between salted/not >>> salted table in case of "primary key leading-part select"? >>> >>> 2016-02-02 1:18 GMT+01:00 Mujtaba Chohan <[email protected]>: >>> >>>> If you are filtering on leading part of row key which is highly >>>> selective then you would be better off not using salt buckets all together >>>> rather than having 100 parallel scan and block reads in your case. In our >>>> test with billion+ row table, non-salted table offer much better >>>> performance since it ends up reading fewer blocks from a single region. >>>> >>>> //mujtaba >>>> >>>> On Mon, Feb 1, 2016 at 1:16 PM, Serega Sheypak < >>>> [email protected]> wrote: >>>> >>>>> Hi, here is my table DDL: >>>>> CREATE TABLE IF NOT EXISTS id_ref >>>>> ( >>>>> id1 VARCHAR NOT NULL, >>>>> value1 VARCHAR, >>>>> >>>>> id2 VARCHAR NOT NULL, >>>>> value2 VARCHAR >>>>> CONSTRAINT id_ref_pk PRIMARY KEY (id1, id2) >>>>> )IMMUTABLE_ROWS=true,SALT_BUCKETS=100, VERSIONS=1, TTL=691200 >>>>> >>>>> I'm trying to analyze result of explain: >>>>> >>>>> explain select id1, value1, id2, value2 from id_ref where id1 = 'xxx' >>>>> >>>>> . . . . . . . . . . . . . . . . . . . . . . .> ; >>>>> >>>>> *+------------------------------------------+* >>>>> >>>>> *| ** PLAN ** |* >>>>> >>>>> *+------------------------------------------+* >>>>> >>>>> *| *CLIENT 100-CHUNK PARALLEL 100-WAY RANGE SCAN OVER ID_REF >>>>> [0,'1fd5c44a75549162ca1602dda55f6d129cab61a6']* |* >>>>> >>>>> *| *CLIENT MERGE SORT * |* >>>>> >>>>> *+------------------------------------------+* >>>>> >>>>> >>>>> What happens? Client spawns 100 parallel scans (because of bucketing) >>>>> and waits for 100 responses? >>>>> >>>>> Is it effective? What is the right way to optimize such query pattern: >>>>> "select by first part of primary key"? Reduce the amount of buckets? I get >>>>> exeption a while after restarting app: >>>>> >>>>> >>>>> *Task org.apache.phoenix.job.JobManager$JobFutureTask@60a40644 >>>>> rejected from org.apache.phoenix.job.JobManager$1@58e3fe9aRunning, pool >>>>> size = 128, active threads = 121, queued tasks = 5000, completed tasks = >>>>> 2629565* >>>>> >>>>> >>>>> >>>> >>> >
