Re: Writing to Parquet Job turns to wait mode after even completion of job

[Chetan Khatri]

Thank you for everyone,  origin question " Every time, i write to parquet.
it shows on Spark UI that stages succeeded but on spark shell it hold
context on wait mode for almost 10 mins. then it clears broadcast,
accumulator shared variables.".

I don't think stopping context can resolve current issue.

It takes more time to clear Broadcast, accumulator etc.

Can we tune up this with spark 1.6.1 MapR distribution.
On Oct 27, 2016 2:34 PM, "Mehrez Alachheb"  wrote:

> I think you should just shut down your SparkContext at the end.
> sc.stop()
>
> 2016-10-21 22:47 GMT+02:00 Chetan Khatri :
>
>> Hello Spark Users,
>>
>> I am writing around 10 GB of Processed Data to Parquet where having 1 TB
>> of HDD and 102 GB of RAM, 16 vCore machine on Google Cloud.
>>
>> Every time, i write to parquet. it shows on Spark UI that stages
>> succeeded but on spark shell it hold context on wait mode for almost 10
>> mins. then it clears broadcast, accumulator shared variables.
>>
>> Can we sped up this thing ?
>>
>> Thanks.
>>
>> --
>> Yours Aye,
>> Chetan Khatri.
>> M.+91 7 80574
>> Data Science Researcher
>> INDIA
>>
>> ​​Statement of Confidentiality
>> 
>> The contents of this e-mail message and any attachments are confidential
>> and are intended solely for addressee. The information may also be legally
>> privileged. This transmission is sent in trust, for the sole purpose of
>> delivery to the intended recipient. If you have received this transmission
>> in error, any use, reproduction or dissemination of this transmission is
>> strictly prohibited. If you are not the intended recipient, please
>> immediately notify the sender by reply e-mail or phone and delete this
>> message and its attachments, if any.​​
>>
>
>

Re: Writing to Parquet Job turns to wait mode after even completion of job

[Mehrez Alachheb]

I think you should just shut down your SparkContext at the end.
sc.stop()

2016-10-21 22:47 GMT+02:00 Chetan Khatri :

> Hello Spark Users,
>
> I am writing around 10 GB of Processed Data to Parquet where having 1 TB
> of HDD and 102 GB of RAM, 16 vCore machine on Google Cloud.
>
> Every time, i write to parquet. it shows on Spark UI that stages succeeded
> but on spark shell it hold context on wait mode for almost 10 mins. then it
> clears broadcast, accumulator shared variables.
>
> Can we sped up this thing ?
>
> Thanks.
>
> --
> Yours Aye,
> Chetan Khatri.
> M.+91 7 80574
> Data Science Researcher
> INDIA
>
> ​​Statement of Confidentiality
> 
> The contents of this e-mail message and any attachments are confidential
> and are intended solely for addressee. The information may also be legally
> privileged. This transmission is sent in trust, for the sole purpose of
> delivery to the intended recipient. If you have received this transmission
> in error, any use, reproduction or dissemination of this transmission is
> strictly prohibited. If you are not the intended recipient, please
> immediately notify the sender by reply e-mail or phone and delete this
> message and its attachments, if any.​​
>

Re: Writing to Parquet Job turns to wait mode after even completion of job

[Steve Loughran]

On 24 Oct 2016, at 20:32, Cheng Lian 
> wrote:



On 10/22/16 6:18 AM, Steve Loughran wrote:

...
On Sat, Oct 22, 2016 at 3:41 AM, Cheng Lian 
> wrote:

What version of Spark are you using and how many output files does the job 
writes out?

By default, Spark versions before 1.6 (not including) writes Parquet summary 
files when committing the job. This process reads footers from all Parquet 
files in the destination directory and merges them together. This can be 
particularly bad if you are appending a small amount of data to a large 
existing Parquet dataset.

If that's the case, you may disable Parquet summary files by setting Hadoop 
configuration " parquet.enable.summary-metadata" to false.


Now I'm a bit mixed up. Should that be 
spark.sql.parquet.enable.summary-metadata =false?
No, "parquet.enable.summary-metadata" is a Hadoop configuration option 
introduced by Parquet. In Spark 2.0, you can simply set it using 
spark.conf.set(), Spark will propagate it properly.


OK, chased it down to  a feature that ryanb @ netflix made optional, presumably 
for their s3 work (PARQUET-107 )

This is what I'm going to say make a good set of options for S3A & Parquet

spark.sql.parquet.filterPushdown true
spark.sql.parquet.mergeSchema false
spark.hadoop.parquet.enable.summary-metadata false

While for ORC, you want


spark.sql.orc.splits.include.file.footer true
spark.sql.orc.cache.stripe.details.size 1
spark.sql.orc.filterPushdown true

And:

spark.sql.hive.metastorePartitionPruning true

along with commitment via:

spark.speculation false
spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version 2
spark.hadoop.mapreduce.fileoutputcommitter.cleanup.skipped true



For when people get to play with the Hadoop S3A phase II binaries, they'll also 
be wanting

spark.hadoop.fs.s3a.readahead.range 157810688

// faster backward seek for ORC and Parquet input
spark.hadoop.fs.s3a.experimental.input.fadvise random

// PUT blocks in separate threads
spark.hadoop.fs.s3a.fast.output.enabled true


the fadvise one is *really* good when working with ORC/Parquet; without that 
column filtering and predicate pushdown is somewhat crippled.

Re: Writing to Parquet Job turns to wait mode after even completion of job

[Cheng Lian]

On 10/22/16 6:18 AM, Steve Loughran wrote:

...
On Sat, Oct 22, 2016 at 3:41 AM, Cheng Lian > wrote:


What version of Spark are you using and how many output files
does the job writes out?

By default, Spark versions before 1.6 (not including) writes
Parquet summary files when committing the job. This process reads
footers from all Parquet files in the destination directory and
merges them together. This can be particularly bad if you are
appending a small amount of data to a large existing Parquet dataset.

If that's the case, you may disable Parquet summary files by
setting Hadoop configuration " parquet.enable.summary-metadata"
to false.




Now I'm a bit mixed up. Should that be 
spark.sql.parquet.enable.summary-metadata =false?
No, "parquet.enable.summary-metadata" is a Hadoop configuration option 
introduced by Parquet. In Spark 2.0, you can simply set it using 
spark.conf.set(), Spark will propagate it properly.



We've disabled it by default since 1.6.0

Cheng


On 10/21/16 1:47 PM, Chetan Khatri wrote:

Hello Spark Users,

I am writing around 10 GB of Processed Data to Parquet where
having 1 TB of HDD and 102 GB of RAM, 16 vCore machine on Google
Cloud.

Every time, i write to parquet. it shows on Spark UI that stages
succeeded but on spark shell it hold context on wait mode for
almost 10 mins. then it clears broadcast, accumulator shared
variables.

Can we sped up this thing ?

Thanks.

-- 
Yours Aye,

Chetan Khatri.
M.+91 7 80574
Data Science Researcher
INDIA

​​Statement of Confidentiality

The contents of this e-mail message and any attachments are
confidential and are intended solely for addressee. The
information may also be legally privileged. This transmission is
sent in trust, for the sole purpose of delivery to the intended
recipient. If you have received this transmission in error, any
use, reproduction or dissemination of this transmission is
strictly prohibited. If you are not the intended recipient,
please immediately notify the sender by reply e-mail or phone
and delete this message and its attachments, if any.​​





--
Yours Aye,
Chetan Khatri.
M.+91 7 80574
Data Science Researcher
INDIA

​​Statement of Confidentiality

The contents of this e-mail message and any attachments are 
confidential and are intended solely for addressee. The information 
may also be legally privileged. This transmission is sent in trust, 
for the sole purpose of delivery to the intended recipient. If you 
have received this transmission in error, any use, reproduction or 
dissemination of this transmission is strictly prohibited. If you are 
not the intended recipient, please immediately notify the sender by 
reply e-mail or phone and delete this message and its attachments, if 
any.​​

Re: Writing to Parquet Job turns to wait mode after even completion of job

[Steve Loughran]

On 22 Oct 2016, at 00:48, Chetan Khatri 
> wrote:

Hello Cheng,

Thank you for response.

I am using spark 1.6.1, i am writing around 350 gz parquet part files for 
single table. Processed around 180 GB of Data using Spark.

Are you writing to GCS storage to to the local HDD?

Regarding options to set, for performance reads against object store hosted 
parquet data, also go for

spark.sql.parquet.filterPushdown true
spark.sql.parquet.mergeSchema false






On Sat, Oct 22, 2016 at 3:41 AM, Cheng Lian 
> wrote:

What version of Spark are you using and how many output files does the job 
writes out?

By default, Spark versions before 1.6 (not including) writes Parquet summary 
files when committing the job. This process reads footers from all Parquet 
files in the destination directory and merges them together. This can be 
particularly bad if you are appending a small amount of data to a large 
existing Parquet dataset.

If that's the case, you may disable Parquet summary files by setting Hadoop 
configuration " parquet.enable.summary-metadata" to false.


Now I'm a bit mixed up. Should that be 
spark.sql.parquet.enable.summary-metadata =false?


We've disabled it by default since 1.6.0

Cheng

On 10/21/16 1:47 PM, Chetan Khatri wrote:
Hello Spark Users,

I am writing around 10 GB of Processed Data to Parquet where having 1 TB of HDD 
and 102 GB of RAM, 16 vCore machine on Google Cloud.

Every time, i write to parquet. it shows on Spark UI that stages succeeded but 
on spark shell it hold context on wait mode for almost 10 mins. then it clears 
broadcast, accumulator shared variables.

Can we sped up this thing ?

Thanks.

--
Yours Aye,
Chetan Khatri.
M.+91 7 80574
Data Science Researcher
INDIA

​​Statement of Confidentiality

The contents of this e-mail message and any attachments are confidential and 
are intended solely for addressee. The information may also be legally 
privileged. This transmission is sent in trust, for the sole purpose of 
delivery to the intended recipient. If you have received this transmission in 
error, any use, reproduction or dissemination of this transmission is strictly 
prohibited. If you are not the intended recipient, please immediately notify 
the sender by reply e-mail or phone and delete this message and its 
attachments, if any.​​




--
Yours Aye,
Chetan Khatri.
M.+91 7 80574
Data Science Researcher
INDIA

​​Statement of Confidentiality

The contents of this e-mail message and any attachments are confidential and 
are intended solely for addressee. The information may also be legally 
privileged. This transmission is sent in trust, for the sole purpose of 
delivery to the intended recipient. If you have received this transmission in 
error, any use, reproduction or dissemination of this transmission is strictly 
prohibited. If you are not the intended recipient, please immediately notify 
the sender by reply e-mail or phone and delete this message and its 
attachments, if any.​​

Re: Writing to Parquet Job turns to wait mode after even completion of job

[Chetan Khatri]

Hello Cheng,

Thank you for response.

I am using spark 1.6.1, i am writing around 350 gz parquet part files for
single table. Processed around 180 GB of Data using Spark.



On Sat, Oct 22, 2016 at 3:41 AM, Cheng Lian  wrote:

> What version of Spark are you using and how many output files does the job
> writes out?
>
> By default, Spark versions before 1.6 (not including) writes Parquet
> summary files when committing the job. This process reads footers from all
> Parquet files in the destination directory and merges them together. This
> can be particularly bad if you are appending a small amount of data to a
> large existing Parquet dataset.
>
> If that's the case, you may disable Parquet summary files by setting
> Hadoop configuration " parquet.enable.summary-metadata" to false.
>
> We've disabled it by default since 1.6.0
>
> Cheng
>
> On 10/21/16 1:47 PM, Chetan Khatri wrote:
>
> Hello Spark Users,
>
> I am writing around 10 GB of Processed Data to Parquet where having 1 TB
> of HDD and 102 GB of RAM, 16 vCore machine on Google Cloud.
>
> Every time, i write to parquet. it shows on Spark UI that stages succeeded
> but on spark shell it hold context on wait mode for almost 10 mins. then it
> clears broadcast, accumulator shared variables.
>
> Can we sped up this thing ?
>
> Thanks.
>
> --
> Yours Aye,
> Chetan Khatri.
> M.+91 7 80574
> Data Science Researcher
> INDIA
>
> ​​Statement of Confidentiality
> 
> The contents of this e-mail message and any attachments are confidential
> and are intended solely for addressee. The information may also be legally
> privileged. This transmission is sent in trust, for the sole purpose of
> delivery to the intended recipient. If you have received this transmission
> in error, any use, reproduction or dissemination of this transmission is
> strictly prohibited. If you are not the intended recipient, please
> immediately notify the sender by reply e-mail or phone and delete this
> message and its attachments, if any.​​
>
>
>


-- 
Yours Aye,
Chetan Khatri.
M.+91 7 80574
Data Science Researcher
INDIA

​​Statement of Confidentiality

The contents of this e-mail message and any attachments are confidential
and are intended solely for addressee. The information may also be legally
privileged. This transmission is sent in trust, for the sole purpose of
delivery to the intended recipient. If you have received this transmission
in error, any use, reproduction or dissemination of this transmission is
strictly prohibited. If you are not the intended recipient, please
immediately notify the sender by reply e-mail or phone and delete this
message and its attachments, if any.​​

Re: Writing to Parquet Job turns to wait mode after even completion of job

[Cheng Lian]

What version of Spark are you using and how many output files does the 
job writes out?


By default, Spark versions before 1.6 (not including) writes Parquet 
summary files when committing the job. This process reads footers from 
all Parquet files in the destination directory and merges them together. 
This can be particularly bad if you are appending a small amount of data 
to a large existing Parquet dataset.


If that's the case, you may disable Parquet summary files by setting 
Hadoop configuration " parquet.enable.summary-metadata" to false.


We've disabled it by default since 1.6.0

Cheng


On 10/21/16 1:47 PM, Chetan Khatri wrote:

Hello Spark Users,

I am writing around 10 GB of Processed Data to Parquet where having 1 
TB of HDD and 102 GB of RAM, 16 vCore machine on Google Cloud.


Every time, i write to parquet. it shows on Spark UI that stages 
succeeded but on spark shell it hold context on wait mode for almost 
10 mins. then it clears broadcast, accumulator shared variables.


Can we sped up this thing ?

Thanks.

--
Yours Aye,
Chetan Khatri.
M.+91 7 80574
Data Science Researcher
INDIA

​​Statement of Confidentiality

The contents of this e-mail message and any attachments are 
confidential and are intended solely for addressee. The information 
may also be legally privileged. This transmission is sent in trust, 
for the sole purpose of delivery to the intended recipient. If you 
have received this transmission in error, any use, reproduction or 
dissemination of this transmission is strictly prohibited. If you are 
not the intended recipient, please immediately notify the sender by 
reply e-mail or phone and delete this message and its attachments, if 
any.​​