Hi Aaron,
Thanks for your answers. That helped me get a big picture.
Yes, it contains a big row that goes up to 2GB with more than a
million of
columns.
Let me confirm if I correctly understand.
- The stack trace is from Slice By Names query. And the
deserialization is
at the step 3, "Read the row level Bloom Filter", on your blog.
- BloomFilterSerializer#deserialize does readLong iteratively at
each page
of size 4K for a given row, which means it could be 500,000 loops(calls
readLong) for a 2G row(from 1.0.7 source).
Correct?
That makes sense Slice By Names queries against such a wide row
could be CPU
bottleneck. In fact, in our test environment, a
BloomFilterSerializer#deserialize of such a case takes more than
10ms, up to
100ms.
Get a single named column.
Get the first 10 columns using the natural column order.
Get the last 10 columns using the reversed order.
Interesting. A query pattern could make a difference?
We thought the only solutions is to change the data structure(don't
use such
a wide row if it is retrieved by Slice By Names query).
Anyway, will give it a try!
Best,
Takenori
On Sat, Feb 2, 2013 at 2:55 AM, aaron morton
<aa...@thelastpickle.com <mailto:aa...@thelastpickle.com>>
wrote:
5. the problematic Data file contains only 5 to 10 keys data but
large(2.4G)
So very large rows ?
What does nodetool cfstats or cfhistograms say about the row sizes ?
1. what is happening?
I think this is partially large rows and partially the query
pattern, this
is only by roughly correct
http://thelastpickle.com/2011/07/04/Cassandra-Query-Plans/ and my
talk here
http://www.datastax.com/events/cassandrasummit2012/presentations
3. any more info required to proceed?
Do some tests with different query techniques…
Get a single named column.
Get the first 10 columns using the natural column order.
Get the last 10 columns using the reversed order.
Hope that helps.
-----------------
Aaron Morton
Freelance Cassandra Developer
New Zealand
@aaronmorton
http://www.thelastpickle.com
On 31/01/2013, at 7:20 PM, Takenori Sato <ts...@cloudian.com> wrote:
Hi all,
We have a situation that CPU loads on some of our nodes in a
cluster has
spiked occasionally since the last November, which is triggered by
requests
for rows that reside on two specific sstables.
We confirmed the followings(when spiked):
version: 1.0.7(current) <- 0.8.6 <- 0.8.5 <- 0.7.8
jdk: Oracle 1.6.0
1. a profiling showed that BloomFilterSerializer#deserialize was the
hotspot(70% of the total load by running threads)
* the stack trace looked like this(simplified)
90.4% - org.apache.cassandra.db.ReadVerbHandler.doVerb
90.4% - org.apache.cassandra.db.SliceByNamesReadCommand.getRow
...
90.4% -
org.apache.cassandra.db.CollationController.collectTimeOrderedData
...
89.5% -
org.apache.cassandra.db.columniterator.SSTableNamesIterator.read
...
79.9% - org.apache.cassandra.io.sstable.IndexHelper.defreezeBloomFilter
68.9% -
org.apache.cassandra.io.sstable.BloomFilterSerializer.deserialize
66.7% - java.io.DataInputStream.readLong
2. Usually, 1 should be so fast that a profiling by sampling can not
detect
3. no pressure on Cassandra's VM heap nor on machine in overal
4. a little I/O traffic for our 8 disks/node(up to 100tps/disk by
"iostat
1 1000")
5. the problematic Data file contains only 5 to 10 keys data but
large(2.4G)
6. the problematic Filter file size is only 256B(could be normal)
So now, I am trying to read the Filter file in the same way
BloomFilterSerializer#deserialize does as possible as I can, in
order to see
if the file is something wrong.
Could you give me some advise on:
1. what is happening?
2. the best way to simulate the BloomFilterSerializer#deserialize
3. any more info required to proceed?
Thanks,
Takenori
