Re: how to get random rows from a big hbase table faster
1% from 1B is 10M. 10M random reads is doable if : a. Cluster is sufficiently large b. equipped with SSDs c. you run multiple clients in parallel to retrieve these rows You need to know in advance min/max rows in a table, then generate randomly start row and open scanner with this start row, then just read first KV Or, say split min/max row region into N consecutive sub-regions (N is up to you) and open N scanners with RandomRowFilter again, you have to run N clients (or threads) to do this in parallel -Vlad On Thu, Apr 12, 2018 at 9:16 AM, Liu, Ming (Ming) wrote: > Hi, all, > > We have a hbase table which has 1 billion rows, and we want to randomly > get 1M from that table. We are now trying the RandomRowFilter, but it is > still very slow. If I understand it correctly, in the Server side, > RandomRowFilter still need to read all 1 billions but return randomly 1% > for them. But read 1 billion rows is very slow. Is this true? > > So is there any other better way to randomly get 1% rows from a given > table? Any idea will be very appreciated. > We don't know the distribution of the 1 billion rows in advance. > > Thanks, > Ming >
Re: how to get random rows from a big hbase table faster
The problem seems related to sampling, a short answer would be based on Spark RDD.sample If RDD.sample is still too slow for your requirement, then maybe https://en.wikipedia.org/wiki/Reservoir_sampling is the direction to investigate, but not sure any existing implementation yet. Reservoir sampling - Wikipedia<https://en.wikipedia.org/wiki/Reservoir_sampling> en.wikipedia.org Reservoir sampling is a family of randomized algorithms for randomly choosing a sample of k items from a list S containing n items, where n is either a very large or unknown number. From: Liu, Ming (Ming) Sent: Friday, April 13, 2018 12:16:07 AM To: user@hbase.apache.org Subject: how to get random rows from a big hbase table faster Hi, all, We have a hbase table which has 1 billion rows, and we want to randomly get 1M from that table. We are now trying the RandomRowFilter, but it is still very slow. If I understand it correctly, in the Server side, RandomRowFilter still need to read all 1 billions but return randomly 1% for them. But read 1 billion rows is very slow. Is this true? So is there any other better way to randomly get 1% rows from a given table? Any idea will be very appreciated. We don't know the distribution of the 1 billion rows in advance. Thanks, Ming
how to get random rows from a big hbase table faster
Hi, all, We have a hbase table which has 1 billion rows, and we want to randomly get 1M from that table. We are now trying the RandomRowFilter, but it is still very slow. If I understand it correctly, in the Server side, RandomRowFilter still need to read all 1 billions but return randomly 1% for them. But read 1 billion rows is very slow. Is this true? So is there any other better way to randomly get 1% rows from a given table? Any idea will be very appreciated. We don't know the distribution of the 1 billion rows in advance. Thanks, Ming
