Re: Read operations resulting in a write?
AFAIK there is no way to disable hoisting. Feel free to let your jira fingers do the talking. Cheers - Aaron Morton Freelance Cassandra Developer New Zealand @aaronmorton http://www.thelastpickle.com On 18/12/2012, at 6:10 PM, Edward Capriolo edlinuxg...@gmail.com wrote: Is there a way to turn this on and off through configuration? I am not necessarily sure I would want this feature. Also it is confusing if these writes show up in JMX and look like user generated write operations. On Mon, Dec 17, 2012 at 10:01 AM, Mike mthero...@yahoo.com wrote: Thank you Aaron, this was very helpful. Could it be an issue that this optimization does not really take effect until the memtable with the hoisted data is flushed? In my simple example below, the same row is updated and multiple selects of the same row will result in multiple writes to the memtable. It seems it maybe possible (although unlikely) where, if you go from a write-mostly to a read-mostly scenario, you could get into a state where you are stuck rewriting to the same memtable, and the memtable is not flushed because it absorbs the over-writes. I can foresee this especially if you are reading the same rows repeatedly. I also noticed from the codepaths that if Row caching is enabled, this optimization will not occur. We made some changes this weekend to make this column family more suitable to row-caching and enabled row-caching with a small cache. Our initial results is that it seems to have corrected the write counts, and has increased performance quite a bit. However, are there any hidden gotcha's there because this optimization is not occurring? https://issues.apache.org/jira/browse/CASSANDRA-2503 mentions a compaction is behind problem. Any history on that? I couldn't find too much information on it. Thanks, -Mike On 12/16/2012 8:41 PM, aaron morton wrote: 1) Am I reading things correctly? Yes. If you do a read/slice by name and more than min compaction level nodes where read the data is re-written so that the next read uses fewer SSTables. 2) What is really happening here? Essentially minor compactions can occur between 4 and 32 memtable flushes. Looking through the code, this seems to only effect a couple types of select statements (when selecting a specific column on a specific key being one of them). During the time between these two values, every select statement will perform a write. Yup, only for readying a row where the column names are specified. Remember minor compaction when using SizedTiered Compaction (the default) works on buckets of the same size. Imagine a row that had been around for a while and had fragments in more than Min Compaction Threshold sstables. Say it is 3 SSTables in the 2nd tier and 2 sstables in the 1st. So it takes (potentially) 5 SSTable reads. If this row is read it will get hoisted back up. But the row has is in only 1 SSTable in the 2nd tier and 2 in the 1st tier it will not hoisted. There are a few short circuits in the SliceByName read path. One of them is to end the search when we know that no other SSTables contain columns that should be considered. So if the 4 columns you read frequently are hoisted into the 1st bucket your reads will get handled by that one bucket. It's not every select. Just those that touched more the min compaction sstables. 3) Is this desired behavior? Is there something else I should be looking at that could be causing this behavior? Yes. https://issues.apache.org/jira/browse/CASSANDRA-2503 Cheers - Aaron Morton Freelance Cassandra Developer New Zealand @aaronmorton http://www.thelastpickle.com On 15/12/2012, at 12:58 PM, Michael Theroux mthero...@yahoo.com wrote: Hello, We have an unusual situation that I believe I've reproduced, at least temporarily, in a test environment. I also think I see where this issue is occurring in the code. We have a specific column family that is under heavy read and write load on a nightly basis. For the purposes of this description, I'll refer to this column family as Bob. During this nightly processing, sometimes Bob is under very write load, other times it is very heavy read load. The application is such that when something is written to Bob, a write is made to one of two other tables. We've witnessed a situation where the write count on Bob far outstrips the write count on either of the other tables, by a factor of 3-10. This is based on the WriteCount available on the column family JMX MBean. We have not been able to find where in our code this is happening, and we have gone as far as tracing our CQL calls to determine that the relationship between Bob and the other tables are what we expect. I brought up a test node to experiment, and see a situation where, when a select statement is executed, a write will occur.
Re: Read operations resulting in a write?
Thank you Aaron, this was very helpful. Could it be an issue that this optimization does not really take effect until the memtable with the hoisted data is flushed? In my simple example below, the same row is updated and multiple selects of the same row will result in multiple writes to the memtable. It seems it maybe possible (although unlikely) where, if you go from a write-mostly to a read-mostly scenario, you could get into a state where you are stuck rewriting to the same memtable, and the memtable is not flushed because it absorbs the over-writes. I can foresee this especially if you are reading the same rows repeatedly. I also noticed from the codepaths that if Row caching is enabled, this optimization will not occur. We made some changes this weekend to make this column family more suitable to row-caching and enabled row-caching with a small cache. Our initial results is that it seems to have corrected the write counts, and has increased performance quite a bit. However, are there any hidden gotcha's there because this optimization is not occurring? https://issues.apache.org/jira/browse/CASSANDRA-2503 mentions a compaction is behind problem. Any history on that? I couldn't find too much information on it. Thanks, -Mike On 12/16/2012 8:41 PM, aaron morton wrote: 1) Am I reading things correctly? Yes. If you do a read/slice by name and more than min compaction level nodes where read the data is re-written so that the next read uses fewer SSTables. 2) What is really happening here? Essentially minor compactions can occur between 4 and 32 memtable flushes. Looking through the code, this seems to only effect a couple types of select statements (when selecting a specific column on a specific key being one of them). During the time between these two values, every select statement will perform a write. Yup, only for readying a row where the column names are specified. Remember minor compaction when using SizedTiered Compaction (the default) works on buckets of the same size. Imagine a row that had been around for a while and had fragments in more than Min Compaction Threshold sstables. Say it is 3 SSTables in the 2nd tier and 2 sstables in the 1st. So it takes (potentially) 5 SSTable reads. If this row is read it will get hoisted back up. But the row has is in only 1 SSTable in the 2nd tier and 2 in the 1st tier it will not hoisted. There are a few short circuits in the SliceByName read path. One of them is to end the search when we know that no other SSTables contain columns that should be considered. So if the 4 columns you read frequently are hoisted into the 1st bucket your reads will get handled by that one bucket. It's not every select. Just those that touched more the min compaction sstables. 3) Is this desired behavior? Is there something else I should be looking at that could be causing this behavior? Yes. https://issues.apache.org/jira/browse/CASSANDRA-2503 Cheers - Aaron Morton Freelance Cassandra Developer New Zealand @aaronmorton http://www.thelastpickle.com On 15/12/2012, at 12:58 PM, Michael Theroux mthero...@yahoo.com mailto:mthero...@yahoo.com wrote: Hello, We have an unusual situation that I believe I've reproduced, at least temporarily, in a test environment. I also think I see where this issue is occurring in the code. We have a specific column family that is under heavy read and write load on a nightly basis. For the purposes of this description, I'll refer to this column family as Bob. During this nightly processing, sometimes Bob is under very write load, other times it is very heavy read load. The application is such that when something is written to Bob, a write is made to one of two other tables. We've witnessed a situation where the write count on Bob far outstrips the write count on either of the other tables, by a factor of 3-10. This is based on the WriteCount available on the column family JMX MBean. We have not been able to find where in our code this is happening, and we have gone as far as tracing our CQL calls to determine that the relationship between Bob and the other tables are what we expect. I brought up a test node to experiment, and see a situation where, when a select statement is executed, a write will occur. In my test, I perform the following (switching between nodetool and cqlsh): update bob set 'about'='coworker' where key='hex key'; nodetool flush update bob set 'about'='coworker' where key='hex key'; nodetool flush update bob set 'about'='coworker' where key='hex key'; nodetool flush update bob set 'about'='coworker' where key='hex key'; nodetool flush update bob set 'about'='coworker' where key='hex key'; nodetool flush Then, for a period of time (before a minor compaction occurs), a select statement that selects specific columns will cause writes to occur in the write count of the column family: select about,changed,data from
Re: Read operations resulting in a write?
Could it be an issue that this optimization does not really take effect until the memtable with the hoisted data is flushed? No. The read path in collectTimeOrderedData() reads from the memtable first. It then reads the SStable meta data (maxTimestamp) and checks if the candidate columns are both 1) all the columns in the query 2) the only possible values . So immediately after the columns are hoisted a read will touch the and the sstable meta data (always in memory) for the most recent sstable. In my simple example below, the same row is updated and multiple selects of the same row will result in multiple writes to the memtable. with some overlapping reads this would be possible, once one of them has completed subsequent operations would read from the memtable only. It seems it maybe possible (although unlikely) where, if you go from a write-mostly to a read-mostly scenario, you could get into a state where you are stuck rewriting to the same memtable, and the memtable is not flushed because it absorbs the over-writes. Memtable would still be flushed due to other CF's generating memory pressure and/or the commit log check pointing. Also reads go to the memtable first. However, are there any hidden gotcha's there because this optimization is not occurring? Not that I can think off, the optimisation is not occurring because all the work getTimeOrderedData() does to read from disk has been done. You're good to to. Assuming you have narrow rows, or a good feel for how big they will get. https://issues.apache.org/jira/browse/CASSANDRA-2503 mentions a compaction is behind problem. Any history on that?I couldn't find too much information on it. I assume it means cases where minor compaction cannot keep up. E.g. it has been throttled down, or a concurrent repair / upgradesstables is slowing things. Cheers - Aaron Morton Freelance Cassandra Developer New Zealand @aaronmorton http://www.thelastpickle.com On 18/12/2012, at 4:01 AM, Mike mthero...@yahoo.com wrote: Thank you Aaron, this was very helpful. Could it be an issue that this optimization does not really take effect until the memtable with the hoisted data is flushed? In my simple example below, the same row is updated and multiple selects of the same row will result in multiple writes to the memtable. It seems it maybe possible (although unlikely) where, if you go from a write-mostly to a read-mostly scenario, you could get into a state where you are stuck rewriting to the same memtable, and the memtable is not flushed because it absorbs the over-writes. I can foresee this especially if you are reading the same rows repeatedly. I also noticed from the codepaths that if Row caching is enabled, this optimization will not occur. We made some changes this weekend to make this column family more suitable to row-caching and enabled row-caching with a small cache. Our initial results is that it seems to have corrected the write counts, and has increased performance quite a bit. However, are there any hidden gotcha's there because this optimization is not occurring? https://issues.apache.org/jira/browse/CASSANDRA-2503 mentions a compaction is behind problem. Any history on that?I couldn't find too much information on it. Thanks, -Mike On 12/16/2012 8:41 PM, aaron morton wrote: 1) Am I reading things correctly? Yes. If you do a read/slice by name and more than min compaction level nodes where read the data is re-written so that the next read uses fewer SSTables. 2) What is really happening here? Essentially minor compactions can occur between 4 and 32 memtable flushes. Looking through the code, this seems to only effect a couple types of select statements (when selecting a specific column on a specific key being one of them). During the time between these two values, every select statement will perform a write. Yup, only for readying a row where the column names are specified. Remember minor compaction when using SizedTiered Compaction (the default) works on buckets of the same size. Imagine a row that had been around for a while and had fragments in more than Min Compaction Threshold sstables. Say it is 3 SSTables in the 2nd tier and 2 sstables in the 1st. So it takes (potentially) 5 SSTable reads. If this row is read it will get hoisted back up. But the row has is in only 1 SSTable in the 2nd tier and 2 in the 1st tier it will not hoisted. There are a few short circuits in the SliceByName read path. One of them is to end the search when we know that no other SSTables contain columns that should be considered. So if the 4 columns you read frequently are hoisted into the 1st bucket your reads will get handled by that one bucket. It's not every select. Just those that touched more the min compaction sstables. 3) Is this desired behavior? Is there something else I
Re: Read operations resulting in a write?
Is there a way to turn this on and off through configuration? I am not necessarily sure I would want this feature. Also it is confusing if these writes show up in JMX and look like user generated write operations. On Mon, Dec 17, 2012 at 10:01 AM, Mike mthero...@yahoo.com wrote: Thank you Aaron, this was very helpful. Could it be an issue that this optimization does not really take effect until the memtable with the hoisted data is flushed? In my simple example below, the same row is updated and multiple selects of the same row will result in multiple writes to the memtable. It seems it maybe possible (although unlikely) where, if you go from a write-mostly to a read-mostly scenario, you could get into a state where you are stuck rewriting to the same memtable, and the memtable is not flushed because it absorbs the over-writes. I can foresee this especially if you are reading the same rows repeatedly. I also noticed from the codepaths that if Row caching is enabled, this optimization will not occur. We made some changes this weekend to make this column family more suitable to row-caching and enabled row-caching with a small cache. Our initial results is that it seems to have corrected the write counts, and has increased performance quite a bit. However, are there any hidden gotcha's there because this optimization is not occurring? https://issues.apache.org/jira/browse/CASSANDRA-2503 mentions a compaction is behind problem. Any history on that? I couldn't find too much information on it. Thanks, -Mike On 12/16/2012 8:41 PM, aaron morton wrote: 1) Am I reading things correctly? Yes. If you do a read/slice by name and more than min compaction level nodes where read the data is re-written so that the next read uses fewer SSTables. 2) What is really happening here? Essentially minor compactions can occur between 4 and 32 memtable flushes. Looking through the code, this seems to only effect a couple types of select statements (when selecting a specific column on a specific key being one of them). During the time between these two values, every select statement will perform a write. Yup, only for readying a row where the column names are specified. Remember minor compaction when using SizedTiered Compaction (the default) works on buckets of the same size. Imagine a row that had been around for a while and had fragments in more than Min Compaction Threshold sstables. Say it is 3 SSTables in the 2nd tier and 2 sstables in the 1st. So it takes (potentially) 5 SSTable reads. If this row is read it will get hoisted back up. But the row has is in only 1 SSTable in the 2nd tier and 2 in the 1st tier it will not hoisted. There are a few short circuits in the SliceByName read path. One of them is to end the search when we know that no other SSTables contain columns that should be considered. So if the 4 columns you read frequently are hoisted into the 1st bucket your reads will get handled by that one bucket. It's not every select. Just those that touched more the min compaction sstables. 3) Is this desired behavior? Is there something else I should be looking at that could be causing this behavior? Yes. https://issues.apache.org/jira/browse/CASSANDRA-2503 Cheers - Aaron Morton Freelance Cassandra Developer New Zealand @aaronmorton http://www.thelastpickle.com On 15/12/2012, at 12:58 PM, Michael Theroux mthero...@yahoo.com wrote: Hello, We have an unusual situation that I believe I've reproduced, at least temporarily, in a test environment. I also think I see where this issue is occurring in the code. We have a specific column family that is under heavy read and write load on a nightly basis. For the purposes of this description, I'll refer to this column family as Bob. During this nightly processing, sometimes Bob is under very write load, other times it is very heavy read load. The application is such that when something is written to Bob, a write is made to one of two other tables. We've witnessed a situation where the write count on Bob far outstrips the write count on either of the other tables, by a factor of 3-10. This is based on the WriteCount available on the column family JMX MBean. We have not been able to find where in our code this is happening, and we have gone as far as tracing our CQL calls to determine that the relationship between Bob and the other tables are what we expect. I brought up a test node to experiment, and see a situation where, when a select statement is executed, a write will occur. In my test, I perform the following (switching between nodetool and cqlsh): update bob set 'about'='coworker' where key='hex key'; nodetool flush update bob set 'about'='coworker' where key='hex key'; nodetool flush update bob set 'about'='coworker' where key='hex key'; nodetool flush update bob set 'about'='coworker' where key='hex
Re: Read operations resulting in a write?
1) Am I reading things correctly?
Yes.
If you do a read/slice by name and more than min compaction level nodes where
read the data is re-written so that the next read uses fewer SSTables.
2) What is really happening here? Essentially minor compactions can occur
between 4 and 32 memtable flushes. Looking through the code, this seems to
only effect a couple types of select statements (when selecting a specific
column on a specific key being one of them). During the time between these
two values, every select statement will perform a write.
Yup, only for readying a row where the column names are specified.
Remember minor compaction when using SizedTiered Compaction (the default) works
on buckets of the same size.
Imagine a row that had been around for a while and had fragments in more than
Min Compaction Threshold sstables. Say it is 3 SSTables in the 2nd tier and 2
sstables in the 1st. So it takes (potentially) 5 SSTable reads. If this row is
read it will get hoisted back up.
But the row has is in only 1 SSTable in the 2nd tier and 2 in the 1st tier it
will not hoisted.
There are a few short circuits in the SliceByName read path. One of them is to
end the search when we know that no other SSTables contain columns that should
be considered. So if the 4 columns you read frequently are hoisted into the 1st
bucket your reads will get handled by that one bucket.
It's not every select. Just those that touched more the min compaction
sstables.
3) Is this desired behavior? Is there something else I should be looking at
that could be causing this behavior?
Yes.
https://issues.apache.org/jira/browse/CASSANDRA-2503
Cheers
-
Aaron Morton
Freelance Cassandra Developer
New Zealand
@aaronmorton
http://www.thelastpickle.com
On 15/12/2012, at 12:58 PM, Michael Theroux mthero...@yahoo.com wrote:
Hello,
We have an unusual situation that I believe I've reproduced, at least
temporarily, in a test environment. I also think I see where this issue is
occurring in the code.
We have a specific column family that is under heavy read and write load on a
nightly basis. For the purposes of this description, I'll refer to this
column family as Bob. During this nightly processing, sometimes Bob is
under very write load, other times it is very heavy read load.
The application is such that when something is written to Bob, a write is
made to one of two other tables. We've witnessed a situation where the write
count on Bob far outstrips the write count on either of the other tables, by
a factor of 3-10. This is based on the WriteCount available on the column
family JMX MBean. We have not been able to find where in our code this is
happening, and we have gone as far as tracing our CQL calls to determine that
the relationship between Bob and the other tables are what we expect.
I brought up a test node to experiment, and see a situation where, when a
select statement is executed, a write will occur.
In my test, I perform the following (switching between nodetool and cqlsh):
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
Then, for a period of time (before a minor compaction occurs), a select
statement that selects specific columns will cause writes to occur in the
write count of the column family:
select about,changed,data from bob where key='hex key';
This situation will continue until a minor compaction is completed.
I went into the code and added some traces to CollationController.java:
private ColumnFamily collectTimeOrderedData()
{
logger.debug(collectTimeOrderedData);
... snip ...
--- HERE logger.debug( tables iterated: + sstablesIterated + Min
compact: + cfs.getMinimumCompactionThreshold() );
// hoist up the requested data into a more recent sstable
if (sstablesIterated cfs.getMinimumCompactionThreshold()
!cfs.isCompactionDisabled()
cfs.getCompactionStrategy() instanceof
SizeTieredCompactionStrategy)
{
RowMutation rm = new RowMutation(cfs.table.name, new
Row(filter.key, returnCF.cloneMe()));
try
{
--- HERE logger.debug( Apply hoisted up row mutation );
// skipping commitlog and index updates is fine since
we're just de-fragmenting existing data
Table.open(rm.getTable()).apply(rm, false, false);
}
catch (IOException e)
{
// log and allow the result to be returned
Read operations resulting in a write?
Hello,
We have an unusual situation that I believe I've reproduced, at least
temporarily, in a test environment. I also think I see where this issue is
occurring in the code.
We have a specific column family that is under heavy read and write load on a
nightly basis. For the purposes of this description, I'll refer to this
column family as Bob. During this nightly processing, sometimes Bob is under
very write load, other times it is very heavy read load.
The application is such that when something is written to Bob, a write is made
to one of two other tables. We've witnessed a situation where the write count
on Bob far outstrips the write count on either of the other tables, by a factor
of 3-10. This is based on the WriteCount available on the column family JMX
MBean. We have not been able to find where in our code this is happening, and
we have gone as far as tracing our CQL calls to determine that the relationship
between Bob and the other tables are what we expect.
I brought up a test node to experiment, and see a situation where, when a
select statement is executed, a write will occur.
In my test, I perform the following (switching between nodetool and cqlsh):
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
update bob set 'about'='coworker' where key='hex key';
nodetool flush
Then, for a period of time (before a minor compaction occurs), a select
statement that selects specific columns will cause writes to occur in the write
count of the column family:
select about,changed,data from bob where key='hex key';
This situation will continue until a minor compaction is completed.
I went into the code and added some traces to CollationController.java:
private ColumnFamily collectTimeOrderedData() {
logger.debug(collectTimeOrderedData); ... snip ...
--- HERE logger.debug( tables iterated: + sstablesIterated + Min
compact: + cfs.getMinimumCompactionThreshold() );
// hoist up the requested data into a more recent sstable if
(sstablesIterated cfs.getMinimumCompactionThreshold()
!cfs.isCompactionDisabled() cfs.getCompactionStrategy() instanceof
SizeTieredCompactionStrategy) { RowMutation rm = new
RowMutation(cfs.table.name, new Row(filter.key, returnCF.cloneMe())); try {
--- HERE logger.debug( Apply hoisted up row mutation );
// skipping commitlog and index updates is fine since we're just de-fragmenting
existing data Table.open(rm.getTable()).apply(rm, false, false); } catch
(IOException e) { // log and allow the result to be returned
logger.error(Error re-writing read results, e); } }
... snip ...
Performing the steps above, I see the following traces (in the test environment
I decreased the minimum compaction threshold to make this easier to reproduce).
After I do a couple of update/flush, I see this in the log:
DEBUG [FlushWriter:7] 2012-12-14 22:54:40,106 CompactionManager.java (line 117)
Scheduling a background task check for bob with SizeTieredCompactionStrategy
Then, until compaction occurs, I see (when performing a select):
DEBUG [ScheduledTasks:1] 2012-12-14 22:55:15,998 LoadBroadcaster.java (line 86)
Disseminating load info ...
DEBUG [Thrift:12] 2012-12-14 22:55:16,990 CassandraServer.java (line 1227)
execute_cql_query
DEBUG [Thrift:12] 2012-12-14 22:55:16,991 QueryProcessor.java (line 445) CQL
statement type: SELECT
DEBUG [Thrift:12] 2012-12-14 22:55:16,991 StorageProxy.java (line 653)
Command/ConsistencyLevel is SliceByNamesReadCommand(table='open',
key=804229d1933669d0a25d2a38c8b26ded10069573003e6dbb1ce21b5f402a5342,
columnParent='QueryPath(columnFamilyName='bob', superColumnName='null',
columnName='null')', columns=[about,changed,data,])/ONE
DEBUG [Thrift:12] 2012-12-14 22:55:16,992 ReadCallback.java (line 79) Blockfor
is 1; setting up requests to /10.0.4.20
DEBUG [Thrift:12] 2012-12-14 22:55:16,992 StorageProxy.java (line 669) reading
data locally
DEBUG [ReadStage:61] 2012-12-14 22:55:16,992 StorageProxy.java (line 813)
LocalReadRunnable reading SliceByNamesReadCommand(table='open',
key=804229d1933669d0a25d2a38c8b26ded10069573003e6dbb1ce21b5f402a5342,
columnParent='QueryPath(columnFamilyName='bob', superColumnName='null',
columnName='null')', columns=[about,changed,data,])
DEBUG [ReadStage:61] 2012-12-14 22:55:16,992 CollationController.java (line 68)
In get top level columns: class org.apache.cassandra.db.filter.NamesQueryFilter
type: Standard valid: class org.apache.cassandra.db.marshal.BytesType
DEBUG [ReadStage:61] 2012-12-14 22:55:16,992 CollationController.java (line 84)
collectTimeOrderedData
--- DEBUG [ReadStage:61] 2012-12-14 22:55:17,192 CollationController.java
(line 188) tables iterated: 4 Min compact: 2
DEBUG [ReadStage:61] 2012-12-14 22:55:17,192
