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From Jeff Jirsa <jji...@gmail.com>
Subject Re: Tombstones in memtable
Date Sun, 24 Feb 2019 16:37:27 GMT
Given your data model, there’s two ways you may read a tombstone:

You select an expired row, or you scan the whole table.

If you select an expired row, you’re going to scan one tombstone. With sufficiently high
read rate, that’ll look like you’re scanning a lot - each read will add one to the histogram
and it may add up to millions in 5 minutes if you’re reading fast enough,  but in this read
pattern it’s not a problem.

If you’re doing a table scan, and you ask for 5000 rows at a time, you may have to scan
past tens of thousands of expired rows to eventually find the 5000 live rows. IF you’re
doing this, it may be a bit concerning, because it’s having to skip past a ton of tombstones
on the read path - which is expensive; this is why the metric exists,  but you’ve said you’re
not doing this.

You’re not going to be able to stop reading tombstones unless you can stop the app from
reading expired rows. But on the plus side, this type of tombstone read is not expensive and
not concerning at all.

-- 
Jeff Jirsa


> On Feb 24, 2019, at 5:36 AM, Rahul Reddy <rahulreddy1234@gmail.com> wrote:
> 
> Thanks Jeff. I'm trying to figure out why the tombstones scans are happening if possible
eliminate it.
> 
>> On Sat, Feb 23, 2019, 10:50 PM Jeff Jirsa <jjirsa@gmail.com> wrote:
>> G1GC with an 8g heap may be slower than CMS. Also you don’t typically set new gen
size on G1.
>> 
>> Again though - what problem are you solving here? If you’re serving reads and sitting
under 50% cpu, it’s not clear to me what you’re trying to fix. Tombstones scanned won’t
matter for your table, so if that’s your only concern, I’d ignore it. 
>> 
>> 
>> 
>> -- 
>> Jeff Jirsa
>> 
>> 
>>> On Feb 23, 2019, at 7:26 PM, Rahul Reddy <rahulreddy1234@gmail.com> wrote:
>>> 
>>> ```jvm setting
>>> 
>>> -XX:+UseThreadPriorities
>>> -XX:ThreadPriorityPolicy=42
>>> -XX:+HeapDumpOnOutOfMemoryError
>>> -Xss256k
>>> -XX:StringTableSize=1000003
>>> -XX:+AlwaysPreTouch
>>> -XX:-UseBiasedLocking
>>> -XX:+UseTLAB
>>> -XX:+ResizeTLAB
>>> -XX:+UseNUMA
>>> -XX:+PerfDisableSharedMem
>>> -Djava.net.preferIPv4Stack=true
>>> -XX:+UseG1GC
>>> -XX:G1RSetUpdatingPauseTimePercent=5
>>> -XX:MaxGCPauseMillis=500
>>> -XX:+PrintGCDetails
>>> -XX:+PrintGCDateStamps
>>> -XX:+PrintHeapAtGC
>>> -XX:+PrintTenuringDistribution
>>> -XX:+PrintGCApplicationStoppedTime
>>> -XX:+PrintPromotionFailure
>>> -XX:+UseGCLogFileRotation
>>> -XX:NumberOfGCLogFiles=10
>>> -XX:GCLogFileSize=10M
>>> 
>>> Total memory
>>> free
>>>              total       used       free     shared    buffers     cached
>>> Mem:      16434004   16125340     308664         60     172872    5565184
>>> -/+ buffers/cache:   10387284    6046720
>>> Swap:            0          0          0
>>> 
>>> Heap settings in cassandra-env.sh
>>> MAX_HEAP_SIZE="8192M"
>>> HEAP_NEWSIZE="800M"
>>> ```
>>> 
>>>> On Sat, Feb 23, 2019, 10:15 PM Rahul Reddy <rahulreddy1234@gmail.com>
wrote:
>>>> Thanks Jeff,
>>>> 
>>>> Since low writes and high reads most of the time data in memtables only.
 When I noticed intially issue no stables on disk everything in memtable only. 
>>>> 
>>>>> On Sat, Feb 23, 2019, 10:01 PM Jeff Jirsa <jjirsa@gmail.com> wrote:
>>>>> Also given your short ttl and low write rate, you may want to think about
how you can keep more in memory - this may mean larger memtable and high flush thresholds
(reading from the memtable), or perhaps the partition cache (if you are likely to read the
same key multiple times). You’ll also probably win some with basic perf and GC tuning, but
can’t really do that via email. Cassandra-8150 has some pointers. 
>>>>> 
>>>>> -- 
>>>>> Jeff Jirsa
>>>>> 
>>>>> 
>>>>>> On Feb 23, 2019, at 6:52 PM, Jeff Jirsa <jjirsa@gmail.com>
wrote:
>>>>>> 
>>>>>> You’ll only ever have one tombstone per read, so your load is based
on normal read rate not tombstones. The metric isn’t wrong, but it’s not indicative of
a problem here given your data model. 
>>>>>> 
>>>>>> You’re using STCS do you may be reading from more than one sstable
if you update column2 for a given column1, otherwise you’re probably just seeing normal
read load. Consider dropping your compression chunk size a bit (given the sizes in your cfstats
I’d probably go to 4K instead of 64k), and maybe consider LCS or TWCS instead of STCS (Which
is appropriate depends on a lot of factors, but STCS is probably causing a fair bit of unnecessary
compactions and probably is very slow to expire data).
>>>>>> 
>>>>>> -- 
>>>>>> Jeff Jirsa
>>>>>> 
>>>>>> 
>>>>>>> On Feb 23, 2019, at 6:31 PM, Rahul Reddy <rahulreddy1234@gmail.com>
wrote:
>>>>>>> 
>>>>>>> Do you see anything wrong with this metric.
>>>>>>> 
>>>>>>> metric to scan tombstones
>>>>>>> increase(cassandra_Table_TombstoneScannedHistogram{keyspace="mykeyspace",Table="tablename",function="Count"}[5m])
>>>>>>> 
>>>>>>> And sametime CPU Spike to 50% whenever I see high tombstone alert.
>>>>>>> 
>>>>>>>> On Sat, Feb 23, 2019, 9:25 PM Jeff Jirsa <jjirsa@gmail.com>
wrote:
>>>>>>>> Your schema is such that you’ll never read more than one
tombstone per select (unless you’re also doing range reads / table scans that you didn’t
mention) - I’m not quite sure what you’re alerting on, but you’re not going to have
tombstone problems with that table / that select. 
>>>>>>>> 
>>>>>>>> -- 
>>>>>>>> Jeff Jirsa
>>>>>>>> 
>>>>>>>> 
>>>>>>>>> On Feb 23, 2019, at 5:55 PM, Rahul Reddy <rahulreddy1234@gmail.com>
wrote:
>>>>>>>>> 
>>>>>>>>> Changing gcgs didn't help
>>>>>>>>> 
>>>>>>>>> CREATE KEYSPACE ksname WITH replication = {'class': 'NetworkTopologyStrategy',
'dc1': '3', 'dc2': '3'}  AND durable_writes = true;
>>>>>>>>> 
>>>>>>>>> 
>>>>>>>>> ```CREATE TABLE keyspace."table" (
>>>>>>>>>     "column1" text PRIMARY KEY,
>>>>>>>>>     "column2" text
>>>>>>>>> ) WITH bloom_filter_fp_chance = 0.01
>>>>>>>>>     AND caching = {'keys': 'ALL', 'rows_per_partition':
'NONE'}
>>>>>>>>>     AND comment = ''
>>>>>>>>>     AND compaction = {'class': 'org.apache.cassandra.db.compaction.SizeTieredCompactionStrategy',
'max_threshold': '32', 'min_threshold': '4'}
>>>>>>>>>     AND compression = {'chunk_length_in_kb': '64', 'class':
'org.apache.cassandra.io.compress.LZ4Compressor'}
>>>>>>>>>     AND crc_check_chance = 1.0
>>>>>>>>>     AND dclocal_read_repair_chance = 0.1
>>>>>>>>>     AND default_time_to_live = 18000
>>>>>>>>>     AND gc_grace_seconds = 60
>>>>>>>>>     AND max_index_interval = 2048
>>>>>>>>>     AND memtable_flush_period_in_ms = 0
>>>>>>>>>     AND min_index_interval = 128
>>>>>>>>>     AND read_repair_chance = 0.0
>>>>>>>>>     AND speculative_retry = '99PERCENTILE';
>>>>>>>>> 
>>>>>>>>> flushed table and took tsstabledump    
>>>>>>>>> grep -i '"expired" : true' SSTables.txt|wc -l
>>>>>>>>> 16439
>>>>>>>>> grep -i '"expired" : false'  SSTables.txt |wc -l
>>>>>>>>> 2657
>>>>>>>>> 
>>>>>>>>> ttl is 4 hours.
>>>>>>>>> 
>>>>>>>>> INSERT INTO keyspace."TABLE_NAME" ("column1", "column2")
VALUES (?, ?) USING TTL(4hours) ?';
>>>>>>>>> SELECT * FROM keyspace."TABLE_NAME" WHERE "column1" =
?';
>>>>>>>>> 
>>>>>>>>> metric to scan tombstones 
>>>>>>>>> increase(cassandra_Table_TombstoneScannedHistogram{keyspace="mykeyspace",Table="tablename",function="Count"}[5m])
>>>>>>>>> 
>>>>>>>>> during peak hours. we only have couple of hundred inserts
and 5-8k reads/s per node.
>>>>>>>>> ```
>>>>>>>>> 
>>>>>>>>> ```tablestats
>>>>>>>>> 	Read Count: 605231874
>>>>>>>>> 	Read Latency: 0.021268529760215503 ms.
>>>>>>>>> 	Write Count: 2763352
>>>>>>>>> 	Write Latency: 0.027924007871599422 ms.
>>>>>>>>> 	Pending Flushes: 0
>>>>>>>>> 		Table: name
>>>>>>>>> 		SSTable count: 1
>>>>>>>>> 		Space used (live): 1413203
>>>>>>>>> 		Space used (total): 1413203
>>>>>>>>> 		Space used by snapshots (total): 0
>>>>>>>>> 		Off heap memory used (total): 28813
>>>>>>>>> 		SSTable Compression Ratio: 0.5015090954531143
>>>>>>>>> 		Number of partitions (estimate): 19568
>>>>>>>>> 		Memtable cell count: 573
>>>>>>>>> 		Memtable data size: 22971
>>>>>>>>> 		Memtable off heap memory used: 0
>>>>>>>>> 		Memtable switch count: 6
>>>>>>>>> 		Local read count: 529868919
>>>>>>>>> 		Local read latency: 0.020 ms
>>>>>>>>> 		Local write count: 2707371
>>>>>>>>> 		Local write latency: 0.024 ms
>>>>>>>>> 		Pending flushes: 0
>>>>>>>>> 		Percent repaired: 0.0
>>>>>>>>> 		Bloom filter false positives: 1
>>>>>>>>> 		Bloom filter false ratio: 0.00000
>>>>>>>>> 		Bloom filter space used: 23888
>>>>>>>>> 		Bloom filter off heap memory used: 23880
>>>>>>>>> 		Index summary off heap memory used: 4717
>>>>>>>>> 		Compression metadata off heap memory used: 216
>>>>>>>>> 		Compacted partition minimum bytes: 73
>>>>>>>>> 		Compacted partition maximum bytes: 124
>>>>>>>>> 		Compacted partition mean bytes: 99
>>>>>>>>> 		Average live cells per slice (last five minutes): 1.0
>>>>>>>>> 		Maximum live cells per slice (last five minutes): 1
>>>>>>>>> 		Average tombstones per slice (last five minutes): 1.0
>>>>>>>>> 		Maximum tombstones per slice (last five minutes): 1
>>>>>>>>> 		Dropped Mutations: 0
>>>>>>>>> 		
>>>>>>>>> 		histograms
>>>>>>>>> Percentile  SSTables     Write Latency      Read Latency
   Partition Size        Cell Count
>>>>>>>>>                               (micros)          (micros)
          (bytes)                  
>>>>>>>>> 50%             0.00             20.50             17.08
               86                 1
>>>>>>>>> 75%             0.00             24.60             20.50
              124                 1
>>>>>>>>> 95%             0.00             35.43             29.52
              124                 1
>>>>>>>>> 98%             0.00             35.43             42.51
              124                 1
>>>>>>>>> 99%             0.00             42.51             51.01
              124                 1
>>>>>>>>> Min             0.00              8.24              5.72
               73                 0
>>>>>>>>> Max             1.00             42.51            152.32
              124                 1
>>>>>>>>> ```
>>>>>>>>> 
>>>>>>>>> 3 node in dc1 and 3 node in dc2 cluster. With instanc
type aws  ec2 m4.xlarge
>>>>>>>>> 
>>>>>>>>>> On Sat, Feb 23, 2019, 7:47 PM Jeff Jirsa <jjirsa@gmail.com>
wrote:
>>>>>>>>>> Would also be good to see your schema (anonymized
if needed) and the select queries you’re running
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>> -- 
>>>>>>>>>> Jeff Jirsa
>>>>>>>>>> 
>>>>>>>>>> 
>>>>>>>>>>> On Feb 23, 2019, at 4:37 PM, Rahul Reddy <rahulreddy1234@gmail.com>
wrote:
>>>>>>>>>>> 
>>>>>>>>>>> Thanks Jeff,
>>>>>>>>>>> 
>>>>>>>>>>> I'm having gcgs set to 10 mins and changed the
table ttl also to 5  hours compared to insert ttl to 4 hours .  Tracing on doesn't show any
tombstone scans for the reads.  And also log doesn't show tombstone scan alerts. Has the reads
are happening 5-8k reads per node during the peak hours it shows 1M tombstone scans count
per read. 
>>>>>>>>>>> 
>>>>>>>>>>>> On Fri, Feb 22, 2019, 11:46 AM Jeff Jirsa
<jjirsa@gmail.com> wrote:
>>>>>>>>>>>> If all of your data is TTL’d and you never
explicitly delete a cell without using s TTL, you can probably drop your GCGS to 1 hour (or
less).
>>>>>>>>>>>> 
>>>>>>>>>>>> Which compaction strategy are you using?
You need a way to clear out those tombstones. There exist tombstone compaction sub properties
that can help encourage compaction to grab sstables just because they’re full of tombstones
which will probably help you.
>>>>>>>>>>>> 
>>>>>>>>>>>> 
>>>>>>>>>>>> -- 
>>>>>>>>>>>> Jeff Jirsa
>>>>>>>>>>>> 
>>>>>>>>>>>> 
>>>>>>>>>>>>> On Feb 22, 2019, at 8:37 AM, Kenneth
Brotman <kenbrotman@yahoo.com.invalid> wrote:
>>>>>>>>>>>>> 
>>>>>>>>>>>>> Can we see the histogram?  Why wouldn’t
you at times have that many tombstones?  Makes sense.
>>>>>>>>>>>>> 
>>>>>>>>>>>>>  
>>>>>>>>>>>>> 
>>>>>>>>>>>>> Kenneth Brotman
>>>>>>>>>>>>> 
>>>>>>>>>>>>>  
>>>>>>>>>>>>> 
>>>>>>>>>>>>> From: Rahul Reddy [mailto:rahulreddy1234@gmail.com]

>>>>>>>>>>>>> Sent: Thursday, February 21, 2019 7:06
AM
>>>>>>>>>>>>> To: user@cassandra.apache.org
>>>>>>>>>>>>> Subject: Tombstones in memtable
>>>>>>>>>>>>> 
>>>>>>>>>>>>>  
>>>>>>>>>>>>> 
>>>>>>>>>>>>> We have small table records are about
5k .
>>>>>>>>>>>>> 
>>>>>>>>>>>>> All the inserts comes as 4hr ttl and
we have table level ttl 1 day and gc grace seconds has 3 hours.  We do 5k reads a second during
peak load During the peak load seeing Alerts for tomstone scanned histogram reaching million.
>>>>>>>>>>>>> 
>>>>>>>>>>>>> Cassandra version 3.11.1. Please let
me know how can this tombstone scan can be avoided in memtable

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