Hi Anil, thanks again for the useful info. My replies inline as well:
On 30/09/15 23:45, anil gupta wrote:
Please find my reply inline.
On Wed, Sep 30, 2015 at 3:29 PM, Konstantinos Kougios
<[email protected] <mailto:[email protected]>>
wrote:
Thanks for the reply and the useful information Anil.
I am aware of the difficulties of distributed joins and
aggregations and that phoenix is a layer on top of hbase. It would
be great if it could be configured to run the queries, even if it
takes a lot of time for the queries to complete.
Anil: I think, it is doable. But, this might require little bit of hit
& trial with HBase and Phoenix conf. I would start with increasing
HBase and Phoenix timeouts.
I believe I did that and now my queries run for a long time without
timeout exceptions (before failing):
zookeeper.session.timeout = 9000000 # not sure if this should be so high
hbase.client.pause = 10000
hbase.client.retries.number = 2
hbase.client.scanner.timeout.period = 6000000
phoenix.query.timeoutMs = 60000000
phoenix.query.keepAliveMs = 60000
hbase.client.operation.timeout = 60000000
hbase.client.backpressure.enabled = true
hbase.client.retries.number = 1
hbase.rpc.timeout = 6000000
failure might all be due to
2015-10-01 09:13:22,002 WARN
[B.defaultRpcServer.handler=14,queue=2,port=16020] ipc.RpcServer:
(responseTooSlow):
{"call":"Scan(org.apache.hadoop.hbase.protobuf.generated.ClientProtos$ScanRequest)","starttimems":1443685974126,"responsesize":10,"method":"Scan","processingtimems":1227740,"client":"192.168.0.11:34656","queuetimems":0,"class":"HRegionServer"}
2015-10-01 09:13:22,296 ERROR
[IndexRpcServer.handler=15,queue=0,port=16020] ipc.RpcServer: Unexpected
throwable object
java.lang.ArrayIndexOutOfBoundsException
at org.apache.hadoop.hbase.util.Bytes.putBytes(Bytes.java:299)
at
org.apache.hadoop.hbase.KeyValue.createByteArray(KeyValue.java:1102)
at org.apache.hadoop.hbase.KeyValue.<init>(KeyValue.java:650)
at org.apache.hadoop.hbase.KeyValue.<init>(KeyValue.java:578)
at
org.apache.phoenix.util.KeyValueUtil.newKeyValue(KeyValueUtil.java:63)
at
org.apache.phoenix.cache.aggcache.SpillManager.getAggregators(SpillManager.java:204)
at
org.apache.phoenix.cache.aggcache.SpillManager.toCacheEntry(SpillManager.java:243)
at
org.apache.phoenix.cache.aggcache.SpillableGroupByCache$EntryIterator.next(SpillableGroupByCache.java:285)
at
org.apache.phoenix.cache.aggcache.SpillableGroupByCache$EntryIterator.next(SpillableGroupByCache.java:261)
at
org.apache.phoenix.cache.aggcache.SpillableGroupByCache$2.next(SpillableGroupByCache.java:364)
at
org.apache.phoenix.coprocessor.BaseRegionScanner.next(BaseRegionScanner.java:40)
at
org.apache.phoenix.coprocessor.BaseRegionScanner.nextRaw(BaseRegionScanner.java:60)
at
org.apache.phoenix.coprocessor.DelegateRegionScanner.nextRaw(DelegateRegionScanner.java:77)
at
org.apache.hadoop.hbase.regionserver.RSRpcServices.scan(RSRpcServices.java:2395)
at
org.apache.hadoop.hbase.protobuf.generated.ClientProtos$ClientService$2.callBlockingMethod(ClientProtos.java:32205)
at org.apache.hadoop.hbase.ipc.RpcServer.call(RpcServer.java:2114)
at org.apache.hadoop.hbase.ipc.CallRunner.run(CallRunner.java:101)
at
org.apache.hadoop.hbase.ipc.RpcExecutor.consumerLoop(RpcExecutor.java:130)
at
org.apache.hadoop.hbase.ipc.RpcExecutor$1.run(RpcExecutor.java:107)
at java.lang.Thread.run(Thread.java:745)
The exception appears frequently in the logs when I run the query.
Also an other issue I've noticed is that sqlline.py starts using the cpu
quite a lot after running my query for a while. Is't that just the
client and should just wait for the server to respond? I believe it is
due of using all it's memory (4GB). Also I think it is writing a lot of
files under /tmp ... is it doing part of the query???
Thanks
I got mainly 2 tables of 170GB and 550GB. Aggregation queries on
both fail and even make region servers crash (there is no info in
the logs and still don't know why. My server proved to be rock
stable so far on other things but you never know).
Anil: RS should not crash. Are you doing heavy writes along with full
table scans at same time? In one of your email, i saw stack trace
regarding Region split and compactions?
I used to, but now I am just trying to run a query without any other
load on the server. Or create an index.
I am doing full table scans only because so far I was unable to
create the indexes. I tried async indexes too with the map reduce
job to create them but it runs extremely slowly.
Anil: This doesnt not sounds good. I haven't use those yet. So, i wont
be able to help debug the problem. Hopefully, someone else will be
able to chime in.
In theory full table scans are possible with hbase, so even if it
was slow it shouldn't fail.
Anil: IMO, if you are doing full table scans, then maybe you should
turn off blockCache for those queries. Basically, there is a lot of
cache churn due to full table scans. Cache churn will lead to JVM GC's.
My setup is a 64GB AMD opteron server with 16 cores. 3 lxc virtual
machines as region servers with Xmx8G, each running on a 3TB
7200rpm disk. So somehow I simulate 3x low spec servers with
enough ram.
Next thing I will try is give region servers 16GB of RAM. WIth 8GB
they seem to have some memory pressure and I see some slow GC's in
the logs.
Anil: 16GB ram should help in some cases. Try to disable blockcache
for full table scans.
Cheers
On 30/09/15 21:18, anil gupta wrote:
Hi Konstantinos,
Please find my reply inline.
On Wed, Sep 30, 2015 at 12:10 PM, Konstantinos Kougios
<[email protected]
<mailto:[email protected]>> wrote:
Hi all,
I had various issues with big tables while experimenting the
couple last weeks.
The thing that goes to my mind is that hbase (+phoenix) works
only when there is a fairly powerful cluster and say 1/2 the
data can fit into the combined servers memory and disks are
fast (SSD?) as well. It doesn't seem to be able to work when
tables are 2x as large as the memory allocated to region
servers (frankly I think it is less)
Anil: Phoenix is just a SQL layer over HBase. From the query in
your previous emails, it seems like you are doing full table
scans with group by clauses. IMO, HBase is not a DB to be used
for full table scans. If 90% of your use cases are small range
scan or gets then HBase should work nicely with Terabytes of
data. I have a 40 TB table in prod on 60 node cluster where every
RS only has 16GB of heap. What kind of workload you are trying to
run with HBase?
Things that constantly fail:
- non-trivial queries on large tables (with group by, counts,
joins) with region server out of memory errors or crashes
without any reason for Xmx of 4G or 8G
Anil: Can you convert these queries into short range based scans?
If you are always going to do full table scan, then maybe you
need to use MR or Spark for those computation and then tune
cluster for full table scans. Cluster tuning varies with full
table scan workload.
- index creation on the same big tables. Those always fail I
think around the point when hbase has to flush it's memory
regions to the disk and couldn't find a solution
- spark jobs fail unless they are throttled to feed hbase
with the data it can take . No backpressure?
There were no replies to my emails regarding the issues,
which makes me think there aren't solutions (or solutions are
pretty hard to find and not many ppl know them).
So after 21 tweaks to the default config, I am still not able
to operate it as a normal database.
Anil: HBase is actually not a normal RDBMS DB. Its a **keyvalue
store**. Phoenix is providing a SQL layer using HBase API. So,
user will need to deal with pros/cons of a key/value store.
Should I start believing my config is all wrong or that
hbase+phoenix is only working if there is a sufficiently
powerful cluster to handle the data?
Anil: **As per my experience**, HBase+Phoenix will work nicely if
you are doing keyvalue lookups and short range scans.
I would suggest you to evaluate data model of HBase tables and
try to convert queries to small range scan or lookups.
I believe it is a great project and the functionality is
really useful. What's lacking is 3 sample configs for 3
different strength clusters.
Anil: I agree that guidance on configuration of HBase and Phoenix
can be improved so that people can get going quickly.
Thanks
--
Thanks & Regards,
Anil Gupta
--
Thanks & Regards,
Anil Gupta
