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From PRAVEEN DEVERACHETTY <pravee...@gmail.com>
Subject Re: Performace issue
Date Wed, 13 Feb 2019 15:58:38 GMT
As per my understanding with Apache drill, it is based on the file store
only. Please help me if i can create any plugins for the following use case
1. Create a json object and push to Apache drill in memory(cache). I can
create json object in java, and if any api available from drill to push
this file in the memory?
2. Read the file from the the memory(cahce) and execute queries by using
that json object from the memory instead of the from the file system or any
data store.

is it possible to do with apache drill? It would be really helpful to
understand the changes i need to make.

thanks,
Praveen

On Wed, Feb 13, 2019 at 11:46 AM PRAVEEN DEVERACHETTY <praveendk@gmail.com>
wrote:

> Hi Sorabh, Data is in json string format, sent over rest api. Using
> convert_from function to convert json string to json array and flatten the
> result array into multiple rows. Data is not stored in the disk. All data
> is in the memory.
>
> Thanks,
> Praveen
>
> On Tue, Feb 12, 2019 at 11:49 PM Sorabh Hamirwasia <
> sohami.apache@gmail.com> wrote:
>
>> Hi Praveen,
>> Can you also share what is the schema of your entire dataset and in what
>> format it's stored?
>>
>> Thanks,
>> Sorabh
>>
>> On Tue, Feb 12, 2019 at 10:02 AM Kunal Khatua <kunal@apache.org> wrote:
>>
>> > You'll need to edit the memory settings in DRILL_HOME/conf/drill-env.sh
>> > I suspect that your 5MB JSON data might be having a lot of objects,
>> which
>> > need to be serialized in memory.
>> >
>> > FLATTEN has the problem that it replicates the data parent data for each
>> > child node that is being flattened into a row... so the resulting data
>> > being constructed in memory can grow significantly.
>> > One way to work around (not elegant, but worth trying) would be to
>> > generate intermediate flatten data and write temporary (if not using
>> WebUI)
>> > tables and keep flattening out those records until you have a fully
>> > flattened dataset to work with directly.
>> >
>> > On 2/11/2019 10:37:58 PM, PRAVEEN DEVERACHETTY <praveendk@gmail.com>
>> > wrote:
>> > Thnks a lot Kunal. I am looking into that. I have one observation.
>> >
>> > With out flatten also, i tried to run a query of size 5MB, it is taking
>> 5GB
>> > of heap? how do i control heap? Are there any settings i can modify. i
>> am
>> > reading a lot, but nothing is working for me. It would be helpful how to
>> > control heap, i modified memory parameters based on the documentation,
>> it
>> > is not working yet. it would be really helpful if i get some help in
>> this
>> > regard. Thanks in advance.
>> >
>> > Regards
>> > Praveen
>> >
>> > On Tue, Feb 12, 2019 at 11:18 AM Kunal Khatua wrote:
>> >
>> > > This is a good starting point for understanding LATERAL-UNNEST and
>> how it
>> > > compares to the FLATTEN operator.
>> > >
>> > > https://drill.apache.org/docs/lateral-join/
>> > >
>> > >
>> > > On 2/11/2019 9:03:42 PM, PRAVEEN DEVERACHETTY wrote:
>> > > Thanks Kunal.
>> > > i am not getting how to use lateral-unrest as dataset does not have
>> child
>> > > rows. All data is in array of json objects(as mentioned below). There
>> are
>> > > two json objects separated by comma and enclosed in squre bracket.
>> > >
>> > >
>> >
>> [{"Location":"100","FirstName":"test1"},{"Location":"100","FirstName":"test2"},{"Location":"101","FirstName":"test3"}]
>> > >
>> > > We are using drill from Java. Through a rest invocation. Not using
>> json
>> > > files. All data is sent over post as string. We are using convert_from
>> > > function in the query to convert into json objects. As we are sending
>> > array
>> > > of json objects, using FLATTEN operator to convert into multiple
>> rows. is
>> > > there any way to avoid Flatten, as we see huge spike for 54MB data,
>> going
>> > > to 24GB and still failing with heap error. not sure what is wrong.
>> Can i
>> > > use FLATTEN on the entire data set? There are almost 54K records that
>> is
>> > > getting FLATTENED.
>> > >
>> > > example query: 1)first converted into array of json objects 2)
>> flatten to
>> > > convert into multiple rows
>> > > select ems.* from (select flatten(t.jdata) as record from (select
>> > >
>> > >
>> >
>> convert_from('[{"Location":"100","FirstName":"test1"},{"Location":"100","FirstName":"test2"},{"Location":"101","FirstName":"test3"}..]')
>> > > as jdata) as t) ems
>> > >
>> > >
>> > > On Sat, Feb 9, 2019 at 1:37 AM Kunal Khatua wrote:
>> > >
>> > > > The memory (heap) would climb as it tries to flatten the JSON data.
>> > Have
>> > > > you tried looking at Drill's LateralJoin-Unnest feature? It was
>> meant
>> > to
>> > > > address memory issues for some use cases of the FLATTEN operator.
>> > > >
>> > > > On 2/8/2019 5:17:01 AM, PRAVEEN DEVERACHETTY wrote:
>> > > > I am running a query with UNION ALL. as below
>> > > >
>> > > > select
>> > > > from ( select FLATTEN(t.jdata) as record from
>> > > > ((select convert_from(json string, json) union all
>> > > > (select conver_from(json_string,json) union all
>> > > > ...
>> > > > ) as jdata) ) as t) ems
>> > > >
>> > > > Reason for giving union all is because we are invoking a call using
>> > rest
>> > > > app, there is limitation of 20,000 when we use convert_from
>> function.
>> > Our
>> > > > heap size is 8GB, server is 8core. From profiling, it shows this
>> > > perticula
>> > > > query spikes from 100MB to 8GB continuously. is there anything i am
>> > > > doing wrong?.
>> > > >
>> > > > Thanks,
>> > > > Prveen
>> > > >
>> > >
>> >
>>
>

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