Re: High Bloom filter false ratio

[Jeff Jirsa]

There exists a JMX endpoint called forceUserDefinedCompaction that takes a 
comma separated list of sstables to compact together.

There also exists a tool called sstablemetadata (may be in a ‘cassandra-tools’ 
package separate from whatever package you used to install cassandra, or in the 
tools/ directory of your binary package). Using sstablemetadata, you can look 
at the maxTimestamp for each table, and the ‘Estimated droppable tombstones’. 
Using those two fields, you could, very easily, write a script that gives you a 
list of sstables that you could feed to forceUserDefinedCompaction to join 
together to eliminate leftover waste.

Your long ParNew times may be fixable by increasing the new gen size of your 
heap – the general guidance in cassandra-env.sh is out of date, you may want to 
reference CASSANDRA-8150 for “newer” advice ( 
http://issues.apache.org/jira/browse/CASSANDRA-8150 ) 

- Jeff

From:  Anishek Agarwal
Reply-To:  "user@cassandra.apache.org"
Date:  Monday, February 22, 2016 at 8:33 PM
To:  "user@cassandra.apache.org"
Subject:  Re: High Bloom filter false ratio

Hey Jeff, 

Thanks for the clarification, I did not explain my self clearly, the 
max_stable_age_days is set to 30 days and the ttl on every insert is set to 30 
days also by default. gc_grace_seconds is 0, so i would think the sstable as a 
whole would be deleted.

Because of the problems mentioned by at 1) above it looks like, there might be 
cases where the table just lies around since no compaction is happening on it 
and even though everything is expired it would still not be deleted?

for 3) the average read is pretty good, though the throughput doesn't seem to 
be that great, when no repair is running we get GCIns > 200ms every couple of 
hours once, otherwise its every 10-20 mins 
INFO [ScheduledTasks:1] 2016-02-23 05:15:03,070 GCInspector.java (line 116) GC 
for ParNew: 205 ms for 1 collections, 1712439128 used; max is 7784628224

 INFO [ScheduledTasks:1] 2016-02-23 08:30:47,709 GCInspector.java (line 116) GC 
for ParNew: 242 ms for 1 collections, 1819126928 used; max is 7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:09:55,085 GCInspector.java (line 116) GC 
for ParNew: 374 ms for 1 collections, 1829660304 used; max is 7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:11:21,245 GCInspector.java (line 116) GC 
for ParNew: 419 ms for 1 collections, 2309875224 used; max is 7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:35:50,717 GCInspector.java (line 116) GC 
for ParNew: 231 ms for 1 collections, 2515325328 used; max is 7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:38:47,194 GCInspector.java (line 116) GC 
for ParNew: 252 ms for 1 collections, 1724241952 used; max is 7784628224



our reading patterns are dependent on BF to work efficiently as we do a lot of 
reads for keys that may not exists because its time series and we segregate 
data based on hourly boundary from epoch.


hey Christoper,

yes every row in the stable that should have been deleted has "d" in that 
column. Also the key for one of the row is as 
"key": "00080cdd5edd080006251000"



how do i get it back to normal readable format to get the (long,long) -- 
composite partition key back?

Looks like i have to force a major compaction to delete a lot of data ? are 
there any other solutions ?

thanks
anishek



On Mon, Feb 22, 2016 at 11:21 PM, Jeff Jirsa  wrote:
1) getFullyExpiredSSTables in 2.0 isn’t as thorough as many expect, so it’s 
very likely that some sstables stick around longer than you expect.

2) max_sstable_age_days tells cassandra when to stop compacting that file, not 
when to delete it.

3) You can change the window size using both the base_time_seconds parameter 
and max_sstable_age_days parameter (use the former to set the size of the first 
window, and the latter to determine how long before you stop compacting that 
window). It’s somewhat non-intuitive. 

Your read latencies actually look pretty reasonable, are you sure you’re not 
simply hitting GC pauses that cause your queries to run longer than you expect? 
Do you have graphs of GC time (first derivative of total gc time is common for 
tools like graphite), or do you see ‘gcinspector’ in your logs indicating 
pauses > 200ms? 

From: Anishek Agarwal
Reply-To: "user@cassandra.apache.org"
Date: Sunday, February 21, 2016 at 11:13 PM
To: "user@cassandra.apache.org"
Subject: Re: High Bloom filter false ratio

Hey guys, 

Just did some more digging ... looks like DTCS is not removing old data 
completely, I used sstable2json for one such table and saw old data there. we 
have a value of 30 for  max_stable_age_days for the table.

One of the columns showed data as :["2015-12-10 11\\:03+0530:", "56690ea2", 
1449725602552000, "d"] what is the meaning of "d" in the last 
IS_MARKED_FOR_DELETE column ? 

I see data from 10 dec 2015 still there, looks like there are a few issues with 
DTCS, Operationally what choices do i have to 

Re: High Bloom filter false ratio

[Anishek Agarwal]

Hey Jeff,

Thanks for the clarification, I did not explain my self clearly, the
max_stable_age_days
is set to 30 days and the ttl on every insert is set to 30 days also
by default. gc_grace_seconds is 0, so i would think the sstable as a whole
would be deleted.

Because of the problems mentioned by at 1) above it looks like, there might
be cases where the table just lies around since no compaction is happening
on it and even though everything is expired it would still not be deleted?

for 3) the average read is pretty good, though the throughput doesn't seem
to be that great, when no repair is running we get GCIns > 200ms every
couple of hours once, otherwise its every 10-20 mins

INFO [ScheduledTasks:1] 2016-02-23 05:15:03,070 GCInspector.java (line 116)
GC for ParNew: 205 ms for 1 collections, 1712439128 used; max is 7784628224

 INFO [ScheduledTasks:1] 2016-02-23 08:30:47,709 GCInspector.java (line
116) GC for ParNew: 242 ms for 1 collections, 1819126928 used; max is
7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:09:55,085 GCInspector.java (line
116) GC for ParNew: 374 ms for 1 collections, 1829660304 used; max is
7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:11:21,245 GCInspector.java (line
116) GC for ParNew: 419 ms for 1 collections, 2309875224 used; max is
7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:35:50,717 GCInspector.java (line
116) GC for ParNew: 231 ms for 1 collections, 2515325328 used; max is
7784628224

 INFO [ScheduledTasks:1] 2016-02-23 09:38:47,194 GCInspector.java (line
116) GC for ParNew: 252 ms for 1 collections, 1724241952 used; max is
7784628224


our reading patterns are dependent on BF to work efficiently as we do a
lot of reads for keys that may not exists because its time series and
we segregate data based on hourly boundary from epoch.


hey Christoper,

yes every row in the stable that should have been deleted has "d" in that
column. Also the key for one of the row is as

"key": "00080cdd5edd080006251000"



how do i get it back to normal readable format to get the (long,long) --
composite partition key back?

Looks like i have to force a major compaction to delete a lot of data ? are
there any other solutions ?

thanks
anishek



On Mon, Feb 22, 2016 at 11:21 PM, Jeff Jirsa 
wrote:

> 1) getFullyExpiredSSTables in 2.0 isn’t as thorough as many expect, so
> it’s very likely that some sstables stick around longer than you expect.
>
> 2) max_sstable_age_days tells cassandra when to stop compacting that file,
> not when to delete it.
>
> 3) You can change the window size using both the base_time_seconds
> parameter and max_sstable_age_days parameter (use the former to set the
> size of the first window, and the latter to determine how long before you
> stop compacting that window). It’s somewhat non-intuitive.
>
> Your read latencies actually look pretty reasonable, are you sure you’re
> not simply hitting GC pauses that cause your queries to run longer than you
> expect? Do you have graphs of GC time (first derivative of total gc time is
> common for tools like graphite), or do you see ‘gcinspector’ in your logs
> indicating pauses > 200ms?
>
> From: Anishek Agarwal
> Reply-To: "user@cassandra.apache.org"
> Date: Sunday, February 21, 2016 at 11:13 PM
> To: "user@cassandra.apache.org"
> Subject: Re: High Bloom filter false ratio
>
> Hey guys,
>
> Just did some more digging ... looks like DTCS is not removing old data
> completely, I used sstable2json for one such table and saw old data there.
> we have a value of 30 for  max_stable_age_days for the table.
>
> One of the columns showed data as :["2015-12-10 11\\:03+0530:",
> "56690ea2", 1449725602552000, "d"] what is the meaning of "d" in the last
> IS_MARKED_FOR_DELETE column ?
>
> I see data from 10 dec 2015 still there, looks like there are a few issues
> with DTCS, Operationally what choices do i have to rectify this, We are on
> version 2.0.15.
>
> thanks
> anishek
>
>
>
>
> On Mon, Feb 22, 2016 at 10:23 AM, Anishek Agarwal 
> wrote:
>
>> We are using DTCS have a 30 day window for them before they are cleaned
>> up. I don't think with DTCS we can do anything about table sizing. Please
>> do let me know if there are other ideas.
>>
>> On Sat, Feb 20, 2016 at 12:51 AM, Jaydeep Chovatia <
>> chovatia.jayd...@gmail.com> wrote:
>>
>>> To me following three looks on higher side:
>>> SSTable count: 1289
>>>
>>> In order to reduce SSTable count see if you are compacting of not (If
>>> using STCS). Is it possible to change this to LCS?
>>>
>>>
>>> Number of keys (estimate): 345137664 (345M partition keys)
>>>
>>> I don't have any suggestion about reducing this unless you partition
>>> your data.
>>>
>>>
>>> Bloom filter space used, bytes: 493777336 (400MB is huge)
>>>
>>> If number of keys are reduced then this will automatically reduce bloom
>>> filter size I believe.
>>>
>>>
>>>
>>> Jaydeep
>>>
>>> On Thu, Feb 18, 2016 at 7:52 PM, Anishek Agarwal 

Isolation for atomic batch on the same partition key

[Yawei Li]

Hi all,
A couple of questions about atomic batch:

1. If  an atomic batch (logged batch) contains a bunch of row mutations and
all of them have the same partition key, can I assume all those changes
have the same isolation as the row-level isolation? According to the post
here http://www.mail-archive.com/user%40cassandra.apache.org/msg42434.html,
it seems that we can get strong isolation.
e.g.
*BEGIN BATCH*
*  UPDATE a IF condition_1;*
*  INSERT b;*
*  INSERT c;*
*APPLY BATCH*

So at any replica, we expect isolation for the three changes on *a*, *b*,
*c*  (*a* , *b*, *c* have the same partition key *k1*) -- i.e. either none
or all of them are visible. Can someone help confirm?

2. Say in the above batch, we include two extra row mutations d and e for
another partition key *k2*.  Will the changes on (*a*, *b*, *c*)  and (*d*,
*e*) still atomic respectively in terms of isolation? I understand there is
no isolation between (*a*, *b*, *c*) and (*d*, *e*).  I.e. is there a
per-parition-key isolation guaranteed?


3. I assume CL SERIAL or LOCAL_SERIAL on reads will try applying the above
logged batch if it is committed but not applied. Right?

Thanks
Yawei

[Announcement] Achilles 4.1.0 released

[DuyHai Doan]

Hello all

 I am pleased to announce the release of Achilles 4.1.0.

 The biggest change is the support for new Cassandra 3.x Materialized View
by annotation.

Achilles also enforces constraints on your views (all primary key columns
of the base table should be in the view etc..) at compile time and
generates only SELECT query builder (since update/insert is not allowed)


 For more details, the wiki: https://github.com/doanduyhai/Achilles/wiki

Regards

Duy Hai DOAN

Cassandra Calcite integration

[Michael Mior]

Hi all,

For those not familiar, Apache Calcite is a data management framework that
enables storage-agnostic SQL query processing. The practical implications
are that by writing a relatively small amount of code, Calcite can execute
a large subset of SQL queries against different backend databases.

Over the past couple weeks I wrote a Cassandra adapter for Calcite. By just
pointing Calcite at a Cassandra installation, you can execute SQL queries
over the data stored in your Cassandra tables (including joins).

These queries will not necessarily be efficient as it entirely depends on
how your data is modelled in the underlying CQL tables. There's a lot of
work to be done, but I'm hoping this will be helpful to those who want to
do a bit of exploration of their data without writing any code.

I wrote a blog post here that provides more details:
http://michael.mior.ca/blog/calcite-cassandra-adapter/

Cheers,
--
Michael Mior
mm...@uwaterloo.ca

Re: High Bloom filter false ratio

[Jeff Jirsa]

1) getFullyExpiredSSTables in 2.0 isn’t as thorough as many expect, so it’s 
very likely that some sstables stick around longer than you expect.

2) max_sstable_age_days tells cassandra when to stop compacting that file, not 
when to delete it.

3) You can change the window size using both the base_time_seconds parameter 
and max_sstable_age_days parameter (use the former to set the size of the first 
window, and the latter to determine how long before you stop compacting that 
window). It’s somewhat non-intuitive. 

Your read latencies actually look pretty reasonable, are you sure you’re not 
simply hitting GC pauses that cause your queries to run longer than you expect? 
Do you have graphs of GC time (first derivative of total gc time is common for 
tools like graphite), or do you see ‘gcinspector’ in your logs indicating 
pauses > 200ms? 

From:  Anishek Agarwal
Reply-To:  "user@cassandra.apache.org"
Date:  Sunday, February 21, 2016 at 11:13 PM
To:  "user@cassandra.apache.org"
Subject:  Re: High Bloom filter false ratio

Hey guys, 

Just did some more digging ... looks like DTCS is not removing old data 
completely, I used sstable2json for one such table and saw old data there. we 
have a value of 30 for  max_stable_age_days for the table.

One of the columns showed data as :["2015-12-10 11\\:03+0530:", "56690ea2", 
1449725602552000, "d"] what is the meaning of "d" in the last 
IS_MARKED_FOR_DELETE column ? 

I see data from 10 dec 2015 still there, looks like there are a few issues with 
DTCS, Operationally what choices do i have to rectify this, We are on version 
2.0.15.

thanks
anishek




On Mon, Feb 22, 2016 at 10:23 AM, Anishek Agarwal  wrote:
We are using DTCS have a 30 day window for them before they are cleaned up. I 
don't think with DTCS we can do anything about table sizing. Please do let me 
know if there are other ideas.

On Sat, Feb 20, 2016 at 12:51 AM, Jaydeep Chovatia  
wrote:
To me following three looks on higher side: 
SSTable count: 1289
In order to reduce SSTable count see if you are compacting of not (If using 
STCS). Is it possible to change this to LCS?

Number of keys (estimate): 345137664 (345M partition keys)
I don't have any suggestion about reducing this unless you partition your data. 

Bloom filter space used, bytes: 493777336 (400MB is huge)
If number of keys are reduced then this will automatically reduce bloom filter 
size I believe.


Jaydeep

On Thu, Feb 18, 2016 at 7:52 PM, Anishek Agarwal  wrote:
Hey all, 

@Jaydeep here is the cfstats output from one node. 

Read Count: 1721134722

Read Latency: 0.04268825050756254 ms.

Write Count: 56743880

Write Latency: 0.014650376727851532 ms.

Pending Tasks: 0

Table: user_stay_points

SSTable count: 1289

Space used (live), bytes: 122141272262

Space used (total), bytes: 224227850870

Off heap memory used (total), bytes: 653827528

SSTable Compression Ratio: 0.4959736121441446

Number of keys (estimate): 345137664

Memtable cell count: 339034

Memtable data size, bytes: 106558314

Memtable switch count: 3266

Local read count: 1721134803

Local read latency: 0.048 ms

Local write count: 56743898

Local write latency: 0.018 ms

Pending tasks: 0

Bloom filter false positives: 40664437

Bloom filter false ratio: 0.69058

Bloom filter space used, bytes: 493777336

Bloom filter off heap memory used, bytes: 493767024

Index summary off heap memory used, bytes: 91677192

Compression metadata off heap memory used, bytes: 68383312

Compacted partition minimum bytes: 104

Compacted partition maximum bytes: 1629722

Compacted partition mean bytes: 1773

Average live cells per slice (last five minutes): 0.0

Average tombstones per slice (last five minutes): 0.0



@Tyler Hobbs 

we are using cassandra 2.0.15 so 
https://issues.apache.org/jira/browse/CASSANDRA-8525  shouldnt occur. Other 
problems looks like will be fixed in 3.0 .. we will mostly try and slot in an 
upgrade to 3.x version towards second quarter of this year.



@Daemon

Latencies seem to have higher ratios, attached is the graph.



I am mostly trying to look at Bloom filters, because the way we do reads, we 
read data with non existent partition keys and it seems to be taking long to 
respond, like for 720 queries it takes 2 seconds, with all 721 queries not 
returning anything. the 720 queries are done in sequence of 180 queries each 
with 180 of them running in parallel. 



thanks

anishek



On Fri, Feb 19, 2016 at 3:09 AM, Jaydeep Chovatia  
wrote:
How many partition keys exists for the table which shows this problem (or 
provide nodetool cfstats for that table)?

On Thu, Feb 18, 2016 at 11:38 AM, daemeon reiydelle  wrote:

The bloom filter buckets the values in a small number of buckets. I have been 
surprised by how many cases I see with large cardinality where a few values 
populate a given bloom leaf, resulting in high false positives, and a 

Re: High Bloom filter false ratio

[Christopher Bradford]

Does every record in the SSTable have a "d" column?

On Mon, Feb 22, 2016 at 2:14 AM Anishek Agarwal  wrote:

> Hey guys,
>
> Just did some more digging ... looks like DTCS is not removing old data
> completely, I used sstable2json for one such table and saw old data there.
> we have a value of 30 for  max_stable_age_days for the table.
>
> One of the columns showed data as :["2015-12-10 11\\:03+0530:",
> "56690ea2", 1449725602552000, "d"] what is the meaning of "d" in the last
> IS_MARKED_FOR_DELETE column ?
>
> I see data from 10 dec 2015 still there, looks like there are a few issues
> with DTCS, Operationally what choices do i have to rectify this, We are on
> version 2.0.15.
>
> thanks
> anishek
>
>
>
>
> On Mon, Feb 22, 2016 at 10:23 AM, Anishek Agarwal 
> wrote:
>
>> We are using DTCS have a 30 day window for them before they are cleaned
>> up. I don't think with DTCS we can do anything about table sizing. Please
>> do let me know if there are other ideas.
>>
>> On Sat, Feb 20, 2016 at 12:51 AM, Jaydeep Chovatia <
>> chovatia.jayd...@gmail.com> wrote:
>>
>>> To me following three looks on higher side:
>>> SSTable count: 1289
>>>
>>> In order to reduce SSTable count see if you are compacting of not (If
>>> using STCS). Is it possible to change this to LCS?
>>>
>>>
>>> Number of keys (estimate): 345137664 (345M partition keys)
>>>
>>> I don't have any suggestion about reducing this unless you partition
>>> your data.
>>>
>>>
>>> Bloom filter space used, bytes: 493777336 (400MB is huge)
>>>
>>> If number of keys are reduced then this will automatically reduce bloom
>>> filter size I believe.
>>>
>>>
>>>
>>> Jaydeep
>>>
>>> On Thu, Feb 18, 2016 at 7:52 PM, Anishek Agarwal 
>>> wrote:
>>>
 Hey all,

 @Jaydeep here is the cfstats output from one node.

 Read Count: 1721134722

 Read Latency: 0.04268825050756254 ms.

 Write Count: 56743880

 Write Latency: 0.014650376727851532 ms.

 Pending Tasks: 0

 Table: user_stay_points

 SSTable count: 1289

 Space used (live), bytes: 122141272262

 Space used (total), bytes: 224227850870

 Off heap memory used (total), bytes: 653827528

 SSTable Compression Ratio: 0.4959736121441446

 Number of keys (estimate): 345137664

 Memtable cell count: 339034

 Memtable data size, bytes: 106558314

 Memtable switch count: 3266

 Local read count: 1721134803

 Local read latency: 0.048 ms

 Local write count: 56743898

 Local write latency: 0.018 ms

 Pending tasks: 0

 Bloom filter false positives: 40664437

 Bloom filter false ratio: 0.69058

 Bloom filter space used, bytes: 493777336

 Bloom filter off heap memory used, bytes: 493767024

 Index summary off heap memory used, bytes: 91677192

 Compression metadata off heap memory used, bytes: 68383312

 Compacted partition minimum bytes: 104

 Compacted partition maximum bytes: 1629722

 Compacted partition mean bytes: 1773

 Average live cells per slice (last five minutes): 0.0

 Average tombstones per slice (last five minutes): 0.0


 @Tyler Hobbs

 we are using cassandra 2.0.15 so
 https://issues.apache.org/jira/browse/CASSANDRA-8525  shouldnt occur.
 Other problems looks like will be fixed in 3.0 .. we will mostly try and
 slot in an upgrade to 3.x version towards second quarter of this year.


 @Daemon

 Latencies seem to have higher ratios, attached is the graph.


 I am mostly trying to look at Bloom filters, because the way we do
 reads, we read data with non existent partition keys and it seems to be
 taking long to respond, like for 720 queries it takes 2 seconds, with all
 721 queries not returning anything. the 720 queries are done in
 sequence of 180 queries each with 180 of them running in parallel.


 thanks

 anishek



 On Fri, Feb 19, 2016 at 3:09 AM, Jaydeep Chovatia <
 chovatia.jayd...@gmail.com> wrote:

> How many partition keys exists for the table which shows this problem
> (or provide nodetool cfstats for that table)?
>
> On Thu, Feb 18, 2016 at 11:38 AM, daemeon reiydelle <
> daeme...@gmail.com> wrote:
>
>> The bloom filter buckets the values in a small number of buckets. I
>> have been surprised by how many cases I see with large cardinality where 
>> a
>> few values populate a given bloom leaf, resulting in high false 
>> positives,
>> and a surprising impact on latencies!
>>
>> Are you seeing 2:1 ranges between mean and worse case latencies
>> (allowing for gc times)?
>>
>> Daemeon Reiydelle
>> On Feb 18, 2016 8:57 AM, "Tyler Hobbs"  wrote:
>>
>>> You can try