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From S L <slouie.at.w...@gmail.com>
Subject Re: Difference between ResultScanner and initTableMapperJob
Date Tue, 11 Jul 2017 19:18:32 GMT
If I forgot to say, the keys that the log shows is causing the
RetriesExhaustedException should be deleted/gone from the table due to the
TTL being exceeded.

Fri Jul 07 20:23:26 PDT 2017, null, java.net.SocketTimeoutException:
callTimeout=40000, callDuration=40303: row
'41_db160190.iad3.mydomain.com_1486067940' on table 'server_based_data' at
region=server_based_data,41_db160190.iad3.mydomain.com_1486067940,1487094006943.f67c3b9836107bdbe6a533e2829c509a.,
hostname=hslave35150.ams9.mydomain.com,60020,1483579082784, seqNum=5423139

The timestamp here is from Feb 2, 2017.  My TTL is 30 days.  Since I ran
the job on July 7, 2017, Feb 2017 is way past the 30 day TTL

describe 'server_based_data'

Table server_based_data is ENABLED


server_based_data


COLUMN FAMILIES DESCRIPTION


{NAME => 'raw_data', DATA_BLOCK_ENCODING => 'NONE', BLOOMFILTER => 'ROW',
REPLIC

ATION_SCOPE => '0', VERSIONS => '1', COMPRESSION => 'SNAPPY', MIN_VERSIONS
=> '0

', TTL => '2592000 SECONDS (30 DAYS)', KEEP_DELETED_CELLS => 'FALSE',
BLOCKSIZE

=> '65536', IN_MEMORY => 'false', BLOCKCACHE => 'true'}


1 row(s) in 0.5180 seconds

On Tue, Jul 11, 2017 at 12:11 PM, S L <slouie.at.work@gmail.com> wrote:

> Sorry for not being clear.  I tried with both versions, first 1.0.1, then
> 1,2-cdh5.7.2.  We are currently running on Cloudera 5.7.2, thus why I used
> that version of the jar.
>
> I had set the timeout to be as short as 30 sec and as long as 2 min but I
> was still running into the problem.  When setting the timeout to 2 min, the
> job took almost 50 min to "complete".  Complete is in quotes because it
> fails (see pastebin below)
>
> Here's a copy of the hadoop output logs via pastebin.  The log is 11000
> lines so I just pasted up to the first couple exceptions and then pasted
> the end where it jumps from 80% maps to 100% and from 21% reduce to 100%
> because Yarn or something killed it.
>
> https://pastebin.com/KwriyPn6
> http://imgur.com/a/ouPZ5 - screenshot from failed mapreduce job from
> cloudera manager/Yarn
>
>
>
> On Mon, Jul 10, 2017 at 8:50 PM, Ted Yu <yuzhihong@gmail.com> wrote:
>
>> bq. for hbase-client/hbase-server version 1.0.1 and 1.2.0-cdh5.7.2.
>>
>> You mean the error occurred for both versions or, client is on 1.0.1 and
>> server is on 1.2.0 ?
>>
>> There should be more to the RetriesExhaustedException.
>> Can you pastebin the full stack trace ?
>>
>> Cheers
>>
>> On Mon, Jul 10, 2017 at 2:21 PM, S L <slouie.at.work@gmail.com> wrote:
>>
>> > I hope someone can tell me what the difference between these two API
>> calls
>> > are.  I'm getting weird results between the two of them.  This is
>> happening
>> > for hbase-client/hbase-server version 1.0.1 and 1.2.0-cdh5.7.2.
>> >
>> > First off, my rowkeys are in the format hash_name_timestamp
>> > e.g. 100_servername_1234567890.  The hbase table has a TTL of 30 days so
>> > things older than 30 days should disappear after compaction.
>> >
>> > The following is code for using ResultScanner.  It doesn't use
>> MapReduce so
>> > it takes a very long time to complete.  I can't run my job this way
>> because
>> > it takes too long.  However, for debugging purposes, I don't have any
>> > problems with this method.  It lists all keys for the specified time
>> range,
>> > which look valid to me since all the timestamps of the returned keys are
>> > within the past 30 days and within the specified time range:
>> >
>> >     Scan scan = new Scan();
>> >     scan.addColumn(Bytes.toBytes("raw_data"), Bytes.toBytes(fileType));
>> >     scan.setCaching(500);
>> >     scan.setCacheBlocks(false);
>> >     scan.setTimeRange(start, end);
>> >
>> >     Connection fConnection = ConnectionFactory.createConnection(conf);
>> >     Table table = fConnection.getTable(TableName.valueOf(tableName));
>> >     ResultScanner scanner = table.getScanner(scan);
>> >     for (Result result = scanner.next(); result != null; result =
>> > scanner.next()) {
>> >        System.out.println("Found row: " + Bytes.toString(result.getRow()
>> > ));
>> >     }
>> >
>> >
>> > The follow code doesn't work but it uses MapReduce, which runs way
>> faster
>> > than using the ResultScanner way, since it divides things up into 1200
>> > maps.  The problem is I'm getting rowkeys that should have disappeared
>> due
>> > to TTL expiring:
>> >
>> >     Scan scan = new Scan();
>> >     scan.addColumn(Bytes.toBytes("raw_data"), Bytes.toBytes(fileType));
>> >     scan.setCaching(500);
>> >     scan.setCacheBlocks(false);
>> >     scan.setTimeRange(start, end);
>> > TableMapReduceUtil.initTableMapperJob(tableName, scan,
>> MTTRMapper.class,
>> > Text.class, IntWritable.class, job);
>> >
>> > Here is the error that I get, which eventually kills the whole MR job
>> later
>> > because over 25% of the mappers failed.
>> >
>> > > Error: org.apache.hadoop.hbase.client.RetriesExhaustedException:
>> > > Failed after attempts=36, exceptions: Wed Jun 28 13:46:57 PDT 2017,
>> > > null, java.net.SocketTimeoutException: callTimeout=120000,
>> > > callDuration=120301: row '65_app129041.iad1.mydomain.com_1476641940'
>> > > on table 'server_based_data' at region=server_based_data
>> >
>> > I'll try to study the code for the hbase-client and hbase-server jars
>> but
>> > hopefully someone will know offhand what the difference between the
>> methods
>> > are and what is causing the initTableMapperJob call to fail.
>> >
>>
>
>

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