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From Amit Adhau <amit.ad...@globant.com>
Subject Re: Fwd: Partition and Split rows
Date Tue, 17 May 2016 18:47:29 GMT
Hi Casey,

As per Dan's reply as per below it is supported in kudu 0.8, I'm bit
confused now, can you please confirm, so that we can use use either int64
in impala if not supported or use timestamp(but then it is giving error in
0.8).

Q: Are you going to provide the Kimpala merge or kudu timestamp support in
Impala/Tableu in near future.


TIMESTAMP typed columns should work in Impala/Kudu as of the 0.8 release
(the latest), however I know there were a few bugs in the previous
releases.  If your using the latest and are still seeing errors, please
send the error and/or file an issue on JIRA.

Thanks,
Amit
On May 18, 2016 12:03 AM, "Casey Ching" <casey@cloudera.com> wrote:

> Hi Amit,
>
> Impala doesn’t yet support Kudu’s timestamps. I think the best solution we
> have for now is to use Unix time style timestamp values. Impala has
> functions to convert to/from ints/timestamps (example CAST can be used).
>
> Casey
>
> On May 17, 2016 at 12:26:18 AM, Amit Adhau (amit.adhau@globant.com) wrote:
>
> Thanks Dan,
>
> In our CDH 5.7 cluster, we are using Kudu parcel "0.8.0-1.kudu0.8.0.p0.11" and
> Impala_Kudu parcel "2.6.0-1.cdh5.8.0.p0.17".
> we have a table created in kudu using java code as per below;
>
>
> CREATE EXTERNAL TABLE `tablename` (
> `long_value` BIGINT,
> `timestamp_value` TIMESTAMP,
> `string_value` STRING,
>
>
> `addrmetric` STRING
> )
> TBLPROPERTIES(
>   'storage_handler' = 'com.cloudera.kudu.hive.KuduStorageHandler',
>   'kudu.table_name' = 'tablename',
>   'kudu.master_addresses' = 'cluster:7051',
>   'kudu.key_columns' = 'long_value, timestamp_value'
> );
>
> *But, when we try to create the same table in Impala, we are getting below
> error;*
>
> May 17, 4:00:51.477 AM INFO jni-util.cc:177
>
>
> com.cloudera.impala.common.ImpalaRuntimeException: Type TIMESTAMP is not supported in
Kudu
>         at com.cloudera.impala.util.KuduUtil.fromImpalaType(KuduUtil.java:251)
>         at com.cloudera.impala.util.KuduUtil.compareSchema(KuduUtil.java:67)
>         at com.cloudera.impala.catalog.delegates.KuduDdlDelegate.createTable(KuduDdlDelegate.java:87)
>         at com.cloudera.impala.service.CatalogOpExecutor.createTable(CatalogOpExecutor.java:1516)
>         at com.cloudera.impala.service.CatalogOpExecutor.createTable(CatalogOpExecutor.java:1365)
>         at com.cloudera.impala.service.CatalogOpExecutor.execDdlRequest(CatalogOpExecutor.java:249)
>         at com.cloudera.impala.service.JniCatalog.execDdl(JniCatalog.java:131)
>
>
>  May 17, 4:00:51.479 AM INFO status.cc:112
>
>
> ImpalaRuntimeException: Type TIMESTAMP is not supported in Kudu
>
> May 17, 4:00:51.479 AM ERROR catalog-server.cc:64
>
>
> ImpalaRuntimeException: Type TIMESTAMP is not supported in Kudu
>
>
> Can you please help us on the same.
>
> Thanks,
>
> Amit
> ---------- Forwarded message ----------
> From: Dan Burkert <dan@cloudera.com>
> Date: Tue, May 17, 2016 at 2:02 AM
> Subject: Re: Partition and Split rows
> To: user@kudu.incubator.apache.org
>
>
> Hi Amit, responses inline
>
>
>> Q: Can I fetch the kudu Timestamp data from Tableu/Pentaho for reporting
>> and analytics purpose or I need Int64 datatype only.
>>
>
> Is Tableu/Pentaho using Impala to query?  If so, see the answers below.
>
>
>> Q: Are you going to provide the Kimpala merge or kudu timestamp support
>> in Impala/Tableu in near future.
>>
>
> TIMESTAMP typed columns should work in Impala/Kudu as of the 0.8 release
> (the latest), however I know there were a few bugs in the previous
> releases.  If your using the latest and are still seeing errors, please
> send the error and/or file an issue on JIRA.
>
>
>> Q: At this moment, instead of Timestamp we are using Int64 type in kudu,
>> will it be equally helpful for performance, if we use the partition and
>> split by explanation given for timestamp datatype? e.g. can we get a better
>> performance for a composite key on a given kudu table defined as
>> 'metric(s),Int64(has timestamp data) and with a partition on Int64 column
>> with Split by clause?
>>
>
> Internally, the TIMESTAMP type is just an alias to INT64, so it has the
> exact same performance characteristics.  The only difference is how the
> values are displayed in log messages and on the web UI.
>
> - Dan
>
>
>> On Sat, May 7, 2016 at 9:20 PM, Dan Burkert <dan@cloudera.com> wrote:
>>
>>> Hi Sand,
>>>
>>> I've been working on some diagrams to help explain some of the more
>>> advanced partitioning types, it's attached.   Still pretty rough at this
>>> point, but the goal is to clean it up and move it into the Kudu
>>> documentation proper.  I'm interested to hear what kind of time series you
>>> are interested in Kudu for.  I'm tasked with improving Kudu for time
>>> series, you can follow progress here
>>> <https://issues.apache.org/jira/browse/KUDU-1306>. If you have any
>>> additional ideas I'd love to hear them.  You may also be interested in a
>>> small project that a JD and I have been working on in the past week to
>>> build an OpenTSDB style store on top of Kudu, you can find it here
>>> <https://github.com/danburkert/kudu-ts>.  Still quite feature limited
>>> at this point.
>>>
>>> - Dan
>>>
>>> On Fri, May 6, 2016 at 4:51 PM, Sand Stone <sand.m.stone@gmail.com>
>>> wrote:
>>>
>>>> Thanks. Will read.
>>>>
>>>> Given that I am researching time series data, row locality is crucial
>>>> :-)
>>>>
>>>> On Fri, May 6, 2016 at 3:57 PM, Jean-Daniel Cryans <jdcryans@apache.org
>>>> > wrote:
>>>>
>>>>> We do have non-covering range partitions coming in the next few
>>>>> months, here's the design (in review):
>>>>> http://gerrit.cloudera.org:8080/#/c/2772/9/docs/design-docs/non-covering-range-partitions.md
>>>>>
>>>>> The "Background & Motivation" section should give you a good idea
of
>>>>> why I'm mentioning this.
>>>>>
>>>>> Meanwhile, if you don't need row locality, using hash partitioning
>>>>> could be good enough.
>>>>>
>>>>> J-D
>>>>>
>>>>> On Fri, May 6, 2016 at 3:53 PM, Sand Stone <sand.m.stone@gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Makes sense.
>>>>>>
>>>>>> Yeah it would be cool if users could specify/control the split rows
>>>>>> after the table is created. Now, I have to "think ahead" to pre-create
the
>>>>>> range buckets.
>>>>>>
>>>>>> On Fri, May 6, 2016 at 3:49 PM, Jean-Daniel Cryans <
>>>>>> jdcryans@apache.org> wrote:
>>>>>>
>>>>>>> You will only get 1 tablet and no data distribution, which is
bad.
>>>>>>>
>>>>>>> That's also how HBase works, but it will split regions as you
insert
>>>>>>> data and eventually you'll get some data distribution even if
it doesn't
>>>>>>> start in an ideal situation. Tablet splitting will come later
for Kudu.
>>>>>>>
>>>>>>> J-D
>>>>>>>
>>>>>>> On Fri, May 6, 2016 at 3:42 PM, Sand Stone <sand.m.stone@gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> One more questions, how does the range partition work if
I don't
>>>>>>>> specify the split rows?
>>>>>>>>
>>>>>>>> Thanks!
>>>>>>>>
>>>>>>>> On Fri, May 6, 2016 at 3:37 PM, Sand Stone <sand.m.stone@gmail.com>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>> Thanks, Misty. The "advanced" impala example helped.
>>>>>>>>>
>>>>>>>>> I was just reading the Java API,CreateTableOptions.java,
it's
>>>>>>>>> unclear how the range partition column names associated
with the partial
>>>>>>>>> rows params in the addSplitRow API.
>>>>>>>>>
>>>>>>>>> On Fri, May 6, 2016 at 3:08 PM, Misty Stanley-Jones <
>>>>>>>>> mstanleyjones@cloudera.com> wrote:
>>>>>>>>>
>>>>>>>>>> Hi Sand,
>>>>>>>>>>
>>>>>>>>>> Please have a look at
>>>>>>>>>> http://getkudu.io/docs/kudu_impala_integration.html#partitioning_tables
>>>>>>>>>> and see if it is helpful to you.
>>>>>>>>>>
>>>>>>>>>> Thanks,
>>>>>>>>>> Misty
>>>>>>>>>>
>>>>>>>>>> On Fri, May 6, 2016 at 2:00 PM, Sand Stone <
>>>>>>>>>> sand.m.stone@gmail.com> wrote:
>>>>>>>>>>
>>>>>>>>>>> Hi, I am new to Kudu. I wonder how the split
rows work. I know
>>>>>>>>>>> from some docs, this is currently for pre-creation
the table. I am
>>>>>>>>>>> researching how to partition (hash+range) some
time series test data.
>>>>>>>>>>>
>>>>>>>>>>> Is there an example? or notes somewhere I could
read upon.
>>>>>>>>>>>
>>>>>>>>>>> Thanks much.
>>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>>
>> --
>> Thanks & Regards,
>>
>> *Amit Adhau* | Data Architect
>>
>> * GLOBANT* | IND:+91 9821518132
>>
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>
>
>
> --
> Thanks & Regards,
>
> *Amit Adhau* | Data Architect
>
> * GLOBANT* | IND:+91 9821518132
>
> [image: Facebook] <https://www.facebook.com/Globant>
>
> [image: Twitter] <http://www.twitter.com/globant>
>
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>
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is strictly prohibited. If you have received it by mistake please let us 
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La información contenida en este mensaje puede ser confidencial. Ha sido 
enviada para el uso exclusivo del destinatario(s) previsto. Si el lector de 
este mensaje no fuera el destinatario previsto, por el presente queda Ud. 
notificado que cualquier lectura, uso, publicación, diseminación, 
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