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From Tony Dean <Tony.D...@sas.com>
Subject RE: Scan performance
Date Tue, 02 Jul 2013 21:31:21 GMT
The following information is what I discovered from Scan performance testing.

Setup
-------
row key format:
positiion1,position2,position3
where position1 is a fixed literal, and position2 and position3 are variable data.

I have created data with 6000 rows with ~40 columns in each row.  The table contains only
1 column family.

The row that I want to query is:
vid,sid-0,Logon    event:customer value=?

-------

Case 1:
use fully qualified row specification in start/stop row key (e.g., vid,sid-0,Logon) with a
SingleColumnValueFilter in the Scan.

avg response time to get Scan iterator and iterate the single result is ~5ms.  This is expected.


Case 2:
This is the normal case where position2 in the row key is unknown at the time of the query:
vid,?,Logon.
Using a SingleColumnValueFilter in the Scan, the avg response time to get Scan iterator and
iterate the single result is ~100ms.
This is the use case that I'm trying to improve upon.

Case 3:
After upgrading to 0.94.8 I was able to change Case2 by using FuzzyRowFilter instead of SingleColumnValueFilter.
 It's a good candidate since I know position1 and position3.
The avg response time to get Scan iterator and iterate the single result was ~5ms (pretty
much the same response time as case 1 where I knew the complete row key).

I didn't expect such an improvement.  Can you explain how FuzzyRowFilter optimizes scanning
rows from disk?  In my case it needs to scan rows (vid,?,xxxx) until xxxx is greater than
"Logon".  Then it can just stop after that; thereby optimizing the scan, correct?  So, optimization
using FuzzyRowFilter is very dependent upon the data that you are scanning.

Thanks for any insight.


-----Original Message-----
From: lars hofhansl [mailto:larsh@apache.org] 
Sent: Monday, June 24, 2013 5:05 PM
To: user@hbase.apache.org
Subject: Re: Scan performance

RowFilter can help. It depends on the setup.
RowFilter skip all column of the row when the row key does not match.
That will help with IO *if* your rows are larger than the HFile block size (64k by default).
Otherwise it still needs to touch each block.

An HTable does some priming when it is created. The region information for all tables could
be substantial, so it does not make much sense to prime the cache for all tables.
How are you using the client. If you pre-create a reuse HTable and/or HConnection you should
be OK.


-- Lars



________________________________
 From: Tony Dean <Tony.Dean@sas.com>
To: "user@hbase.apache.org" <user@hbase.apache.org>; lars hofhansl <larsh@apache.org>

Sent: Monday, June 24, 2013 1:48 PM
Subject: RE: Scan performance
 

Lars,
I'm waiting for some time to exchange out hbase jars in cluster (that support FuzzyRow filter)
in order to try out.  In the meantime, I'm wondering why RowFilter regex is not more helpful. 
I'm guessing that FuzzyRow filter helps in disk io while Row filter just filters after the
disk io has completed.  Also, I turned on row level bloom filter which does not seem to help
either.

On a different performance note, I'm wondering if there is a way to prime client connection
information and such so that the first client query isn't miserably slow.  After the first
query, response times do get considerably better due to caching necessary information.  Is
there a way to get around this first initial hit?  I assume any such priming would have to
be application specific.

Thanks.

-----Original Message-----
From: lars hofhansl [mailto:larsh@apache.org] 
Sent: Saturday, June 22, 2013 9:24 AM
To: user@hbase.apache.org
Subject: Re: Scan performance

"essential column families" help when you filter on one column but want to return *other*
columns for the rows that matched the column.

Check out HBASE-5416.

-- Lars



________________________________
From: Vladimir Rodionov <vrodionov@carrieriq.com>
To: "user@hbase.apache.org" <user@hbase.apache.org>; lars hofhansl <larsh@apache.org>

Sent: Friday, June 21, 2013 5:00 PM
Subject: RE: Scan performance


Lars,
I thought that column family is the locality group and placement columns which are frequently
accessed together into
the same column family (locality group) is the obvious performance improvement tip. What are
the "essential column families" for in this context?

As for original question..  Unless you place your column into a separate column family in
Table 2, you will
need to scan (load from disk if not cached) ~ 40x more data for the second table (because
you have 40 columns). This may explain why do  see such a difference in
execution time if all data needs to be loaded first from HDFS.

Best regards,
Vladimir Rodionov
Principal Platform Engineer
Carrier IQ, www.carrieriq.com
e-mail: vrodionov@carrieriq.com

________________________________________
From: lars hofhansl [larsh@apache.org]
Sent: Friday, June 21, 2013 3:37 PM
To: user@hbase.apache.org
Subject: Re: Scan performance

HBase is a key value (KV) store. Each column is stored in its own KV, a row is just a set
of KVs that happen to have the row key (which is the first part of the key).
I tried to summarize this here: http://hadoop-hbase.blogspot.de/2011/12/introduction-to-hbase.html)

In the StoreFiles all KVs are sorted in row/column order, but HBase still needs to skip over
many KVs in order to "reach" the next row. So more disk and memory IO is needed.

If you using 0.94 there is a new feature "essential column families". If you always search
by the same column you can place that one in its own column family and all other column in
another column family. In that case your scan performance should be close identical.


-- Lars
________________________________

From: Tony Dean <Tony.Dean@sas.com>
To: "user@hbase.apache.org" <user@hbase.apache.org>
Sent: Friday, June 21, 2013 2:08 PM
Subject: Scan performance




Hi,

I hope that you can shed some light on these 2 scenarios below.

I have 2 small tables of 6000 rows.
Table 1 has only 1 column in each of its rows.
Table 2 has 40 columns in each of its rows.
Other than that the two tables are identical.

In both tables there is only 1 row that contains a matching column that I am filtering on.  
And the Scan performs correctly in both cases by returning only the single result.

The code looks something like the following:

Scan scan = new Scan(startRow, stopRow);   // the start/stop rows should include all 6000
rows
scan.addColumn(cf, qualifier); // only return the column that I am interested in (should only
be in 1 row and only 1 version)

Filter f1 = new InclusiveStopFilter(stopRow);
Filter f2 = new SingleColumnValueFilter(cf, qualifier,  CompareFilter.CompareOp.EQUALS, value);
scan.setFilter(new FilterList(f1, f2));

scan .setTimeRange(0, MAX_LONG);
scan.setMaxVersions(1);

ResultScanner rs = t.getScanner(scan);
for (Result result: rs)
{

}

For table 1, rs.next() takes about 30ms.
For table 2, rs.next() takes about 180ms.

Both are returning the exact same result.  Why is it taking so much longer on table 2 to
get the same result?  The scan depth is the same.  The only difference is the column width. 
But I’m filtering on a single column and returning only that column.

Am I missing something?  As I increase the number of columns, the response time gets worse. 
I do expect the response time to get worse when increasing the number of rows, but not by
increasing the number of columns since I’m returning only 1 column in
both cases.

I appreciate any comments that you have.

-Tony



Tony Dean
SAS Institute Inc.
Principal Software Developer
919-531-6704          …

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