Re: Reading too many tombstones

2015-06-04 Thread Alain RODRIGUEZ 
Actually what happen is that STC as well as LCS mix old and fresh data
during the compaction process.

So all the fragments of the same row that you deleted (or reached the TTL
of), are spread among multiple sstables. The point is that they need to be
gathered all in the same compaction to be really and fully evicted. In a
time series model (using wide rows), there might be quite a few fragments
for each row depending on your sharding on your primary key and on your
insert / update workload. This is due to some issues around distributes
deletes. Tombstones are actually like special inserts, if you remove them
without removing all the fragments of the row, old incorrect data may come
back. So you need to run repairs within the grace period (usually 10 days)
to avoid ghosts (make sure all node has received the tombstone + compact
all the fragments at once (from multiple SSTable) at node level.

Using STCS, the unique way to make sure of this is to run a major
compaction (nodetool compact mykeyspace mycf). But major compaction also
has some negative impacts. If you chose this option, you should read about
it.

An other approach would be to truncate periodically your data. Depending on
your needs, of course...

Anyway this has alway been a tricky issue, handling tombstones (and so
TTLs) properly. That's precisely for this kind of use cases that DTCS was
designed. This strategy keeps data per date which makes a sens for
timeseries and constant TTLs.

See https://labs.spotify.com/2014/12/18/date-tiered-compaction/ and
http://www.datastax.com/dev/blog/datetieredcompactionstrategy

Hope this will help.

NB : I haven't used this (yet ;-)). DTCS is enabled from Cassandra 2.0.11,
you should look at the changelog for some improvements / issues around
 DTCS and imho go directly to the last minor (2.0.15 ?) if you want to use
this compaction strategy.

C*heers,

Alain





2015-06-04 22:31 GMT+02:00 Sebastian Estevez sebastian.este...@datastax.com
:

 Check out the compaction subproperties for tombstones.


 http://docs.datastax.com/en/cql/3.1/cql/cql_reference/compactSubprop.html?scroll=compactSubprop__compactionSubpropertiesDTCS
 On Jun 4, 2015 1:29 PM, Aiman Parvaiz ai...@flipagram.com wrote:

 Thanks Carlos for pointing me in that direction, I have some interesting
 findings to share. So in December last year there was a redesign of
 home_feed and it was migrated to a new CF. Initially all the data in
 home_feed had a TTL of 1 year but migrated data was inserted with TTL of
 30days.
 Now on digging a bit deeper I found that home_feed still has data from
 Jan 2015 with ttl 1275094 (14 days).

 This data is for the same id from home_feed:
  date | ttl(description)
 --+--
  2015-04-03 21:22:58+ |   759791
  2015-04-03 04:50:11+ |   412706
  2015-03-30 22:18:58+ |   759791
  2015-03-29 15:20:36+ |  1978689
  2015-03-28 14:41:28+ |  1275116
  2015-03-28 14:31:25+ |  1275116
  2015-03-18 19:23:44+ |  2512936
  2015-03-13 17:51:01+ |  1978689
  2015-02-12 15:41:01+ |  1978689
  2015-01-18 02:36:27+ |  1275094


 I am not sure what happened in that migration but I think that when
 trying to load data we are reading this old data(as feed queries a
 1000/page to be displayed to the user) and in order to read this data we
 have to cross(read) lots of tombstones(newer data has TTL working
 correctly) and hence the error.
 I am not sure how much would date tier help us in this situation too. If
 anyone has any suggestions in how to handle this either on Systems or
 Developer level please pitch in.

 Thanks

 On Thu, Jun 4, 2015 at 11:47 AM, Carlos Rolo r...@pythian.com wrote:

 The TTL data will only be removed after the gc_grace_seconds. So your
 data with 30 days TTL will be still in Cassandra for 10 days more (40 in
 total). Is your data being there for more than that? Otherwise it is
 expected behaviour and probably you should do something on your data model
 to avoid scanning tombstoned data.

 Regards,

 Carlos Juzarte Rolo
 Cassandra Consultant

 Pythian - Love your data

 rolo@pythian | Twitter: cjrolo | Linkedin: 
 *linkedin.com/in/carlosjuzarterolo
 http://linkedin.com/in/carlosjuzarterolo*
 Mobile: +31 6 159 61 814 | Tel: +1 613 565 8696 x1649
 www.pythian.com

 On Thu, Jun 4, 2015 at 8:31 PM, Aiman Parvaiz ai...@flipagram.com
 wrote:

 yeah we don't update old data. One thing I am curious about is why are
 we running in to so many tombstones with compaction happening normally. Is
 compaction not removing tombstomes?


 On Thu, Jun 4, 2015 at 11:25 AM, Jonathan Haddad j...@jonhaddad.com
 wrote:

 DateTiered is fantastic if you've got time series, TTLed data.  That
 means no updates to old data.

 On Thu, Jun 4, 2015 at 10:58 AM Aiman Parvaiz ai...@flipagram.com
 wrote:

 Hi everyone,
 We are running a 10 node Cassandra 2.0.9 without vnode

Re: Reading too many tombstones

2015-06-04 Thread Jonathan Haddad 
DateTiered is fantastic if you've got time series, TTLed data.  That means
no updates to old data.

On Thu, Jun 4, 2015 at 10:58 AM Aiman Parvaiz ai...@flipagram.com wrote:

 Hi everyone,
 We are running a 10 node Cassandra 2.0.9 without vnode cluster. We are
 running in to a issue where we are reading too many tombstones and hence
 getting tons of WARN messages and some ERROR query aborted.

 cass-prod4 2015-06-04 14:38:34,307 WARN ReadStage:
 https://logentries.com/app/9f95dbd4#1998
 SliceQueryFilter.collectReducedColumns - Read 46 live and 1560 tombstoned
 cells in ABC.home_feed (see tombstone_warn_threshold). 100 columns was
 requested, slices= https://logentries.com/app/9f95dbd4#[-], delInfo=
 https://logentries.com/app/9f95dbd4#{deletedAt=
 https://logentries.com/app/9f95dbd4#-9223372036854775808, localDeletion=
 https://logentries.com/app/9f95dbd4#2147483647}

 cass-prod2 2015-05-31 12:55:55,331 ERROR ReadStage:
 https://logentries.com/app/9f95dbd4#1953
 SliceQueryFilter.collectReducedColumns - Scanned over 10 tombstones in
 ABC.home_feed; query aborted (see tombstone_fail_threshold)

 As you can see all of this is happening for CF home_feed. This CF is
 basically maintaining a feed with TTL set to 2592000 (30 days).
 gc_grace_seconds for this CF is 864000 and its SizeTieredCompaction.

 Repairs have been running regularly and automatic compactions are
 occurring normally too.

 I can definitely use some help here in how to tackle this issue.

 Up till now I have the following ideas:

 1) I can make gc_grace_seconds to 0 and then do a manual compaction for
 this CF and bump up the gc_grace again.

 2) Make gc_grace 0, run manual compaction on this CF and leave gc_grace to
 zero. In this case have to be careful in running repairs.

 3) I am also considering moving to DateTier Compaction.

 What would be the best approach here for my feed case. Any help is
 appreciated.

 Thanks

Re: Reading too many tombstones

2015-06-04 Thread Carlos Rolo 
The TTL data will only be removed after the gc_grace_seconds. So your data
with 30 days TTL will be still in Cassandra for 10 days more (40 in total).
Is your data being there for more than that? Otherwise it is expected
behaviour and probably you should do something on your data model to avoid
scanning tombstoned data.

Regards,

Carlos Juzarte Rolo
Cassandra Consultant

Pythian - Love your data

rolo@pythian | Twitter: cjrolo | Linkedin: *linkedin.com/in/carlosjuzarterolo
http://linkedin.com/in/carlosjuzarterolo*
Mobile: +31 6 159 61 814 | Tel: +1 613 565 8696 x1649
www.pythian.com

On Thu, Jun 4, 2015 at 8:31 PM, Aiman Parvaiz ai...@flipagram.com wrote:

 yeah we don't update old data. One thing I am curious about is why are we
 running in to so many tombstones with compaction happening normally. Is
 compaction not removing tombstomes?


 On Thu, Jun 4, 2015 at 11:25 AM, Jonathan Haddad j...@jonhaddad.com
 wrote:

 DateTiered is fantastic if you've got time series, TTLed data.  That
 means no updates to old data.

 On Thu, Jun 4, 2015 at 10:58 AM Aiman Parvaiz ai...@flipagram.com
 wrote:

 Hi everyone,
 We are running a 10 node Cassandra 2.0.9 without vnode cluster. We are
 running in to a issue where we are reading too many tombstones and hence
 getting tons of WARN messages and some ERROR query aborted.

 cass-prod4 2015-06-04 14:38:34,307 WARN ReadStage:
 https://logentries.com/app/9f95dbd4#1998
 SliceQueryFilter.collectReducedColumns - Read 46 live and 1560 tombstoned
 cells in ABC.home_feed (see tombstone_warn_threshold). 100 columns was
 requested, slices= https://logentries.com/app/9f95dbd4#[-], delInfo=
 https://logentries.com/app/9f95dbd4#{deletedAt=
 https://logentries.com/app/9f95dbd4#-9223372036854775808,
 localDeletion= https://logentries.com/app/9f95dbd4#2147483647}

 cass-prod2 2015-05-31 12:55:55,331 ERROR ReadStage:
 https://logentries.com/app/9f95dbd4#1953
 SliceQueryFilter.collectReducedColumns - Scanned over 10 tombstones in
 ABC.home_feed; query aborted (see tombstone_fail_threshold)

 As you can see all of this is happening for CF home_feed. This CF is
 basically maintaining a feed with TTL set to 2592000 (30 days).
 gc_grace_seconds for this CF is 864000 and its SizeTieredCompaction.

 Repairs have been running regularly and automatic compactions are
 occurring normally too.

 I can definitely use some help here in how to tackle this issue.

 Up till now I have the following ideas:

 1) I can make gc_grace_seconds to 0 and then do a manual compaction for
 this CF and bump up the gc_grace again.

 2) Make gc_grace 0, run manual compaction on this CF and leave gc_grace
 to zero. In this case have to be careful in running repairs.

 3) I am also considering moving to DateTier Compaction.

 What would be the best approach here for my feed case. Any help is
 appreciated.

 Thanks







-- 


--

Re: Reading too many tombstones

2015-06-04 Thread Aiman Parvaiz 
yeah we don't update old data. One thing I am curious about is why are we
running in to so many tombstones with compaction happening normally. Is
compaction not removing tombstomes?

On Thu, Jun 4, 2015 at 11:25 AM, Jonathan Haddad j...@jonhaddad.com wrote:

 DateTiered is fantastic if you've got time series, TTLed data.  That means
 no updates to old data.

 On Thu, Jun 4, 2015 at 10:58 AM Aiman Parvaiz ai...@flipagram.com wrote:

 Hi everyone,
 We are running a 10 node Cassandra 2.0.9 without vnode cluster. We are
 running in to a issue where we are reading too many tombstones and hence
 getting tons of WARN messages and some ERROR query aborted.

 cass-prod4 2015-06-04 14:38:34,307 WARN ReadStage:
 https://logentries.com/app/9f95dbd4#1998
 SliceQueryFilter.collectReducedColumns - Read 46 live and 1560 tombstoned
 cells in ABC.home_feed (see tombstone_warn_threshold). 100 columns was
 requested, slices= https://logentries.com/app/9f95dbd4#[-], delInfo=
 https://logentries.com/app/9f95dbd4#{deletedAt=
 https://logentries.com/app/9f95dbd4#-9223372036854775808,
 localDeletion= https://logentries.com/app/9f95dbd4#2147483647}

 cass-prod2 2015-05-31 12:55:55,331 ERROR ReadStage:
 https://logentries.com/app/9f95dbd4#1953
 SliceQueryFilter.collectReducedColumns - Scanned over 10 tombstones in
 ABC.home_feed; query aborted (see tombstone_fail_threshold)

 As you can see all of this is happening for CF home_feed. This CF is
 basically maintaining a feed with TTL set to 2592000 (30 days).
 gc_grace_seconds for this CF is 864000 and its SizeTieredCompaction.

 Repairs have been running regularly and automatic compactions are
 occurring normally too.

 I can definitely use some help here in how to tackle this issue.

 Up till now I have the following ideas:

 1) I can make gc_grace_seconds to 0 and then do a manual compaction for
 this CF and bump up the gc_grace again.

 2) Make gc_grace 0, run manual compaction on this CF and leave gc_grace
 to zero. In this case have to be careful in running repairs.

 3) I am also considering moving to DateTier Compaction.

 What would be the best approach here for my feed case. Any help is
 appreciated.

 Thanks

Re: Reading too many tombstones

2015-06-04 Thread Sebastian Estevez 
Check out the compaction subproperties for tombstones.

http://docs.datastax.com/en/cql/3.1/cql/cql_reference/compactSubprop.html?scroll=compactSubprop__compactionSubpropertiesDTCS
On Jun 4, 2015 1:29 PM, Aiman Parvaiz ai...@flipagram.com wrote:

 Thanks Carlos for pointing me in that direction, I have some interesting
 findings to share. So in December last year there was a redesign of
 home_feed and it was migrated to a new CF. Initially all the data in
 home_feed had a TTL of 1 year but migrated data was inserted with TTL of
 30days.
 Now on digging a bit deeper I found that home_feed still has data from Jan
 2015 with ttl 1275094 (14 days).

 This data is for the same id from home_feed:
  date | ttl(description)
 --+--
  2015-04-03 21:22:58+ |   759791
  2015-04-03 04:50:11+ |   412706
  2015-03-30 22:18:58+ |   759791
  2015-03-29 15:20:36+ |  1978689
  2015-03-28 14:41:28+ |  1275116
  2015-03-28 14:31:25+ |  1275116
  2015-03-18 19:23:44+ |  2512936
  2015-03-13 17:51:01+ |  1978689
  2015-02-12 15:41:01+ |  1978689
  2015-01-18 02:36:27+ |  1275094


 I am not sure what happened in that migration but I think that when trying
 to load data we are reading this old data(as feed queries a 1000/page to be
 displayed to the user) and in order to read this data we have to
 cross(read) lots of tombstones(newer data has TTL working correctly) and
 hence the error.
 I am not sure how much would date tier help us in this situation too. If
 anyone has any suggestions in how to handle this either on Systems or
 Developer level please pitch in.

 Thanks

 On Thu, Jun 4, 2015 at 11:47 AM, Carlos Rolo r...@pythian.com wrote:

 The TTL data will only be removed after the gc_grace_seconds. So your
 data with 30 days TTL will be still in Cassandra for 10 days more (40 in
 total). Is your data being there for more than that? Otherwise it is
 expected behaviour and probably you should do something on your data model
 to avoid scanning tombstoned data.

 Regards,

 Carlos Juzarte Rolo
 Cassandra Consultant

 Pythian - Love your data

 rolo@pythian | Twitter: cjrolo | Linkedin: *linkedin.com/in/carlosjuzarterolo
 http://linkedin.com/in/carlosjuzarterolo*
 Mobile: +31 6 159 61 814 | Tel: +1 613 565 8696 x1649
 www.pythian.com

 On Thu, Jun 4, 2015 at 8:31 PM, Aiman Parvaiz ai...@flipagram.com
 wrote:

 yeah we don't update old data. One thing I am curious about is why are
 we running in to so many tombstones with compaction happening normally. Is
 compaction not removing tombstomes?


 On Thu, Jun 4, 2015 at 11:25 AM, Jonathan Haddad j...@jonhaddad.com
 wrote:

 DateTiered is fantastic if you've got time series, TTLed data.  That
 means no updates to old data.

 On Thu, Jun 4, 2015 at 10:58 AM Aiman Parvaiz ai...@flipagram.com
 wrote:

 Hi everyone,
 We are running a 10 node Cassandra 2.0.9 without vnode cluster. We are
 running in to a issue where we are reading too many tombstones and hence
 getting tons of WARN messages and some ERROR query aborted.

 cass-prod4 2015-06-04 14:38:34,307 WARN ReadStage:
 https://logentries.com/app/9f95dbd4#1998
 SliceQueryFilter.collectReducedColumns - Read 46 live and 1560 tombstoned
 cells in ABC.home_feed (see tombstone_warn_threshold). 100 columns was
 requested, slices= https://logentries.com/app/9f95dbd4#[-], delInfo=
 https://logentries.com/app/9f95dbd4#{deletedAt=
 https://logentries.com/app/9f95dbd4#-9223372036854775808,
 localDeletion= https://logentries.com/app/9f95dbd4#2147483647}

 cass-prod2 2015-05-31 12:55:55,331 ERROR ReadStage:
 https://logentries.com/app/9f95dbd4#1953
 SliceQueryFilter.collectReducedColumns - Scanned over 10 tombstones in
 ABC.home_feed; query aborted (see tombstone_fail_threshold)

 As you can see all of this is happening for CF home_feed. This CF is
 basically maintaining a feed with TTL set to 2592000 (30 days).
 gc_grace_seconds for this CF is 864000 and its SizeTieredCompaction.

 Repairs have been running regularly and automatic compactions are
 occurring normally too.

 I can definitely use some help here in how to tackle this issue.

 Up till now I have the following ideas:

 1) I can make gc_grace_seconds to 0 and then do a manual compaction
 for this CF and bump up the gc_grace again.

 2) Make gc_grace 0, run manual compaction on this CF and leave
 gc_grace to zero. In this case have to be careful in running repairs.

 3) I am also considering moving to DateTier Compaction.

 What would be the best approach here for my feed case. Any help is
 appreciated.

 Thanks







 --






 --
 Lead Systems Architect
 10351 Santa Monica Blvd, Suite 3310
 Los Angeles CA 90025

Re: Reading too many tombstones

2015-06-04 Thread Aiman Parvaiz 
Thanks Carlos for pointing me in that direction, I have some interesting
findings to share. So in December last year there was a redesign of
home_feed and it was migrated to a new CF. Initially all the data in
home_feed had a TTL of 1 year but migrated data was inserted with TTL of
30days.
Now on digging a bit deeper I found that home_feed still has data from Jan
2015 with ttl 1275094 (14 days).

This data is for the same id from home_feed:
 date | ttl(description)
--+--
 2015-04-03 21:22:58+ |   759791
 2015-04-03 04:50:11+ |   412706
 2015-03-30 22:18:58+ |   759791
 2015-03-29 15:20:36+ |  1978689
 2015-03-28 14:41:28+ |  1275116
 2015-03-28 14:31:25+ |  1275116
 2015-03-18 19:23:44+ |  2512936
 2015-03-13 17:51:01+ |  1978689
 2015-02-12 15:41:01+ |  1978689
 2015-01-18 02:36:27+ |  1275094


I am not sure what happened in that migration but I think that when trying
to load data we are reading this old data(as feed queries a 1000/page to be
displayed to the user) and in order to read this data we have to
cross(read) lots of tombstones(newer data has TTL working correctly) and
hence the error.
I am not sure how much would date tier help us in this situation too. If
anyone has any suggestions in how to handle this either on Systems or
Developer level please pitch in.

Thanks

On Thu, Jun 4, 2015 at 11:47 AM, Carlos Rolo r...@pythian.com wrote:

 The TTL data will only be removed after the gc_grace_seconds. So your data
 with 30 days TTL will be still in Cassandra for 10 days more (40 in total).
 Is your data being there for more than that? Otherwise it is expected
 behaviour and probably you should do something on your data model to avoid
 scanning tombstoned data.

 Regards,

 Carlos Juzarte Rolo
 Cassandra Consultant

 Pythian - Love your data

 rolo@pythian | Twitter: cjrolo | Linkedin: *linkedin.com/in/carlosjuzarterolo
 http://linkedin.com/in/carlosjuzarterolo*
 Mobile: +31 6 159 61 814 | Tel: +1 613 565 8696 x1649
 www.pythian.com

 On Thu, Jun 4, 2015 at 8:31 PM, Aiman Parvaiz ai...@flipagram.com wrote:

 yeah we don't update old data. One thing I am curious about is why are we
 running in to so many tombstones with compaction happening normally. Is
 compaction not removing tombstomes?


 On Thu, Jun 4, 2015 at 11:25 AM, Jonathan Haddad j...@jonhaddad.com
 wrote:

 DateTiered is fantastic if you've got time series, TTLed data.  That
 means no updates to old data.

 On Thu, Jun 4, 2015 at 10:58 AM Aiman Parvaiz ai...@flipagram.com
 wrote:

 Hi everyone,
 We are running a 10 node Cassandra 2.0.9 without vnode cluster. We are
 running in to a issue where we are reading too many tombstones and hence
 getting tons of WARN messages and some ERROR query aborted.

 cass-prod4 2015-06-04 14:38:34,307 WARN ReadStage:
 https://logentries.com/app/9f95dbd4#1998
 SliceQueryFilter.collectReducedColumns - Read 46 live and 1560 tombstoned
 cells in ABC.home_feed (see tombstone_warn_threshold). 100 columns was
 requested, slices= https://logentries.com/app/9f95dbd4#[-], delInfo=
 https://logentries.com/app/9f95dbd4#{deletedAt=
 https://logentries.com/app/9f95dbd4#-9223372036854775808,
 localDeletion= https://logentries.com/app/9f95dbd4#2147483647}

 cass-prod2 2015-05-31 12:55:55,331 ERROR ReadStage:
 https://logentries.com/app/9f95dbd4#1953
 SliceQueryFilter.collectReducedColumns - Scanned over 10 tombstones in
 ABC.home_feed; query aborted (see tombstone_fail_threshold)

 As you can see all of this is happening for CF home_feed. This CF is
 basically maintaining a feed with TTL set to 2592000 (30 days).
 gc_grace_seconds for this CF is 864000 and its SizeTieredCompaction.

 Repairs have been running regularly and automatic compactions are
 occurring normally too.

 I can definitely use some help here in how to tackle this issue.

 Up till now I have the following ideas:

 1) I can make gc_grace_seconds to 0 and then do a manual compaction for
 this CF and bump up the gc_grace again.

 2) Make gc_grace 0, run manual compaction on this CF and leave gc_grace
 to zero. In this case have to be careful in running repairs.

 3) I am also considering moving to DateTier Compaction.

 What would be the best approach here for my feed case. Any help is
 appreciated.

 Thanks







 --






-- 
Lead Systems Architect
10351 Santa Monica Blvd, Suite 3310
Los Angeles CA 90025