Oh sorry, I think I misunderstood you. Looks like the tar.gz file contains
the actual data, not just filenames. Then my suggestion doesn't apply.
On Sun, Jun 11, 2017, 9:54 AM Eugene Kirpichov <kirpic...@google.com> wrote:
> Seems like there's a lot of parallelism you could exploit here and make
> the pipeline much, much faster.
>
> I suggest you:
> 1) in the main program, even before starting the pipeline, read the tar.gz
> file and extract the 4 filenames.
> 2) create the pipeline containing 1 TextIO.Read transform per filename you
> extracted, and Flatten the resulting PCollections
> 3) apply the rest of the pipeline
>
> This way not only you'll be reading 4 files in parallel, but each file
> itself will be read in parallel within the file.
>
> On Sun, Jun 11, 2017, 1:43 AM Morand, Sebastien <
> sebastien.mor...@veolia.com> wrote:
>
>> Hi,
>>
>> It gets a list of filename while building the pipeline (*.tar.gz
>> containing each 4 files).
>>
>> The first step of the pipeline read every line of each files and return a
>> pcollection where each value is a dict containing the content of each file
>> in the archive.
>>
>> Example:
>>
>> - File file1.tar.gz contains file1_A.csv, file1_B.csv, file1_C.csv
>> and file1_D.csv
>> - The first step returns :
>> {
>> "file1_A.csv": [<LIST OF LINES IN file1_A.csv],
>> "file1_B.csv": [<LIST OF LINES IN file1_B.csv],
>> "file1_C.csv": [<LIST OF LINES IN file1_C.csv],
>> "file1_D.csv": [<LIST OF LINES IN file1_D.csv]
>> }
>>
>> => So the first step can be completly parallelized
>>
>>
>> *Sébastien MORAND*
>> Team Lead Solution Architect
>> Technology & Operations / Digital Factory
>> Veolia - Group Information Systems & Technology (IS&T)
>> Cell.: +33 7 52 66 20 81 / Direct: +33 1 85 57 71 08
>> <+33%201%2085%2057%2071%2008>
>> Bureau 0144C (Ouest)
>> 30, rue Madeleine-Vionnet - 93300 Aubervilliers, France
>> *www.veolia.com <http://www.veolia.com>*
>> <http://www.veolia.com>
>> <https://www.facebook.com/veoliaenvironment/>
>> <https://www.youtube.com/user/veoliaenvironnement>
>> <https://www.linkedin.com/company/veolia-environnement>
>> <https://twitter.com/veolia>
>>
>> On 11 June 2017 at 04:01, Eugene Kirpichov <kirpic...@google.com> wrote:
>>
>>> Hi Sebastien,
>>> Can you tell more about how your "step 1" works? I looked at the logs of
>>> your job and it's taking suspiciously long (~20 minutes) to produce the
>>> ~400 elements, and it's doing that sequentially. Is it possible to
>>> parallelize step 1?
>>>
>>> On Sat, Jun 10, 2017 at 5:53 PM Lukasz Cwik <lc...@google.com> wrote:
>>>
>>>> The Dataflow implementation when executing a batch pipeline does not
>>>> parallelize dependent fused segments irrespective of the windowing function
>>>> so #1 will fully execute before #2 starts.
>>>>
>>>> On Sat, Jun 10, 2017 at 3:48 PM, Morand, Sebastien <
>>>> sebastien.mor...@veolia.com> wrote:
>>>>
>>>>> Hi again,
>>>>>
>>>>> So it scales. Now my pipeline is running in two parts:
>>>>>
>>>>> 1. Reading files content (~400) and then GroupByKey
>>>>>
>>>>> 2. From GroupByKey transform and write in bigquery (~50M)
>>>>>
>>>>> 2 is scaling as expected. 1 takes about 25 minutes on my files and 2
>>>>> about 35 minutes scaling. But what if I want to Window so that the second
>>>>> part starts sooner and the process is more parallel?
>>>>>
>>>>> I tried to add a 60 seconds FixedWindow time but it's not working (Job
>>>>> ID : 2017-06-06_04_36_01-9894155361321571250)
>>>>>
>>>>> Regards,
>>>>>
>>>>>
>>>>> *Sébastien MORAND*
>>>>> Team Lead Solution Architect
>>>>> Technology & Operations / Digital Factory
>>>>> Veolia - Group Information Systems & Technology (IS&T)
>>>>> Cell.: +33 7 52 66 20 81 / Direct: +33 1 85 57 71 08
>>>>> <+33%201%2085%2057%2071%2008>
>>>>> Bureau 0144C (Ouest)
>>>>> 30, rue Madeleine-Vionnet - 93300 Aubervilliers, France
>>>>> *www.veolia.com <http://www.veolia.com>*
>>>>> <http://www.veolia.com>
>>>>> <https://www.facebook.com/veoliaenvironment/>
>>>>> <https://www.youtube.com/user/veoliaenvironnement>
>>>>> <https://www.linkedin.com/company/veolia-environnement>
>>>>> <https://twitter.com/veolia>
>>>>>
>>>>> On 6 June 2017 at 01:24, Morand, Sebastien <
>>>>> sebastien.mor...@veolia.com> wrote:
>>>>>
>>>>>> Fine, it scales ... Thank you very much.
>>>>>>
>>>>>> *Sébastien MORAND*
>>>>>> Team Lead Solution Architect
>>>>>> Technology & Operations / Digital Factory
>>>>>> Veolia - Group Information Systems & Technology (IS&T)
>>>>>> Cell.: +33 7 52 66 20 81 / Direct: +33 1 85 57 71 08
>>>>>> <+33%201%2085%2057%2071%2008>
>>>>>> Bureau 0144C (Ouest)
>>>>>> 30, rue Madeleine-Vionnet - 93300 Aubervilliers, France
>>>>>> *www.veolia.com <http://www.veolia.com>*
>>>>>> <http://www.veolia.com>
>>>>>> <https://www.facebook.com/veoliaenvironment/>
>>>>>> <https://www.youtube.com/user/veoliaenvironnement>
>>>>>> <https://www.linkedin.com/company/veolia-environnement>
>>>>>> <https://twitter.com/veolia>
>>>>>>
>>>>>> On 6 June 2017 at 00:31, Morand, Sebastien <
>>>>>> sebastien.mor...@veolia.com> wrote:
>>>>>>
>>>>>>> Thank you Eugene,
>>>>>>>
>>>>>>> I'm trying the Sourabh way (and yours since it looks like it's the
>>>>>>> same idea) and let you know if it's better.
>>>>>>>
>>>>>>> Regards,
>>>>>>>
>>>>>>> *Sébastien MORAND*
>>>>>>> Team Lead Solution Architect
>>>>>>> Technology & Operations / Digital Factory
>>>>>>> Veolia - Group Information Systems & Technology (IS&T)
>>>>>>> Cell.: +33 7 52 66 20 81 / Direct: +33 1 85 57 71 08
>>>>>>> <+33%201%2085%2057%2071%2008>
>>>>>>> Bureau 0144C (Ouest)
>>>>>>> 30, rue Madeleine-Vionnet - 93300 Aubervilliers, France
>>>>>>> *www.veolia.com <http://www.veolia.com>*
>>>>>>> <http://www.veolia.com>
>>>>>>> <https://www.facebook.com/veoliaenvironment/>
>>>>>>> <https://www.youtube.com/user/veoliaenvironnement>
>>>>>>> <https://www.linkedin.com/company/veolia-environnement>
>>>>>>> <https://twitter.com/veolia>
>>>>>>>
>>>>>>> On 5 June 2017 at 23:31, Eugene Kirpichov <kirpic...@google.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> I looked at the job ID you quoted, and yes, it suffers from
>>>>>>>> excessive fusion. I wish we had tooling to automatically detect that
>>>>>>>> and
>>>>>>>> emit a warning, but we don't have that yet.
>>>>>>>>
>>>>>>>> Here's an example of how you can break fusion:
>>>>>>>> https://github.com/apache/beam/blob/master/sdks/java/io/jdbc/src/main/java/org/apache/beam/sdk/io/jdbc/JdbcIO.java#L326-L339
>>>>>>>>
>>>>>>>> On Mon, Jun 5, 2017 at 1:27 PM Sourabh Bajaj <
>>>>>>>> sourabhba...@google.com> wrote:
>>>>>>>>
>>>>>>>>> Yes you're correct.
>>>>>>>>>
>>>>>>>>> On Mon, Jun 5, 2017 at 1:23 PM Morand, Sebastien <
>>>>>>>>> sebastien.mor...@veolia.com> wrote:
>>>>>>>>>
>>>>>>>>>> Between parenthesis of each step I meant the number of records in
>>>>>>>>>> output
>>>>>>>>>>
>>>>>>>>>> When I ungroup I send again the 200 data? not the 20M?
>>>>>>>>>>
>>>>>>>>>> Shouldn't I do instead:
>>>>>>>>>> Read (200) -> GroupByKey (200) -> UnGroup(20M) -> combine (20M)
>>>>>>>>>> -> clean (20M) -> filter (20M) -> insert
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> *Sébastien MORAND*
>>>>>>>>>> Team Lead Solution Architect
>>>>>>>>>> Technology & Operations / Digital Factory
>>>>>>>>>> Veolia - Group Information Systems & Technology (IS&T)
>>>>>>>>>> Cell.: +33 7 52 66 20 81 / Direct: +33 1 85 57 71 08
>>>>>>>>>> <+33%201%2085%2057%2071%2008>
>>>>>>>>>> Bureau 0144C (Ouest)
>>>>>>>>>> 30, rue Madeleine-Vionnet - 93300 Aubervilliers, France
>>>>>>>>>> *www.veolia.com <http://www.veolia.com>*
>>>>>>>>>> <http://www.veolia.com>
>>>>>>>>>> <https://www.facebook.com/veoliaenvironment/>
>>>>>>>>>> <https://www.youtube.com/user/veoliaenvironnement>
>>>>>>>>>> <https://www.linkedin.com/company/veolia-environnement>
>>>>>>>>>> <https://twitter.com/veolia>
>>>>>>>>>>
>>>>>>>>>> On 5 June 2017 at 22:17, Sourabh Bajaj <sourabhba...@google.com>
>>>>>>>>>> wrote:
>>>>>>>>>>
>>>>>>>>>>> I think you need to do something like:
>>>>>>>>>>>
>>>>>>>>>>> Read (200) -> GroupByKey (200) -> UnGroup(200) [Not this can be
>>>>>>>>>>> on 200 different workers] -> combine (20M) -> clean (20M) ->
>>>>>>>>>>> filter (20M) -> insert
>>>>>>>>>>>
>>>>>>>>>>> On Mon, Jun 5, 2017 at 1:14 PM Morand, Sebastien <
>>>>>>>>>>> sebastien.mor...@veolia.com> wrote:
>>>>>>>>>>>
>>>>>>>>>>>> Yes fusion looks like my problem. A job ID to look at:
>>>>>>>>>>>> 2017-06-05_10_14_25-5856213199384263626.
>>>>>>>>>>>>
>>>>>>>>>>>> The point is in your link:
>>>>>>>>>>>> <<
>>>>>>>>>>>> For example, one case in which fusion can limit Dataflow's
>>>>>>>>>>>> ability to optimize worker usage is a "high fan-out" ParDo. In
>>>>>>>>>>>> such an
>>>>>>>>>>>> operation, you might have an input collection with relatively few
>>>>>>>>>>>> elements,
>>>>>>>>>>>> but the ParDo produces an output with hundreds or thousands of
>>>>>>>>>>>> times as
>>>>>>>>>>>> many elements, followed by another ParDo
>>>>>>>>>>>> >>
>>>>>>>>>>>>
>>>>>>>>>>>> This is exactly what I'm doing in the step
>>>>>>>>>>>> transform-combine-7d5ad942 in the above job id.
>>>>>>>>>>>>
>>>>>>>>>>>> As fas as I understand, I should create a GroupByKey after the
>>>>>>>>>>>> transform-combine-7d5ad942 on a unique field and then ungroup the
>>>>>>>>>>>> data?
>>>>>>>>>>>> (meaning I add two operations in the pipeline to help the worker?
>>>>>>>>>>>>
>>>>>>>>>>>> Right now:
>>>>>>>>>>>> Read (200) -> combine (20M) -> clean (20M) -> filter (20M) ->
>>>>>>>>>>>> insert
>>>>>>>>>>>>
>>>>>>>>>>>> Will become:
>>>>>>>>>>>> Read (200) -> combine (20M) -> GroupByKey (20M) -> ungroup
>>>>>>>>>>>> (20M) -> clean (20M) -> filter (20M) -> insert
>>>>>>>>>>>>
>>>>>>>>>>>> It this the right way?
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>>
>>>>>>>>>>>> *Sébastien MORAND*
>>>>>>>>>>>> Team Lead Solution Architect
>>>>>>>>>>>> Technology & Operations / Digital Factory
>>>>>>>>>>>> Veolia - Group Information Systems & Technology (IS&T)
>>>>>>>>>>>> Cell.: +33 7 52 66 20 81 / Direct: +33 1 85 57 71 08
>>>>>>>>>>>> <+33%201%2085%2057%2071%2008>
>>>>>>>>>>>> Bureau 0144C (Ouest)
>>>>>>>>>>>> 30, rue Madeleine-Vionnet - 93300 Aubervilliers, France
>>>>>>>>>>>> *www.veolia.com <http://www.veolia.com>*
>>>>>>>>>>>> <http://www.veolia.com>
>>>>>>>>>>>> <https://www.facebook.com/veoliaenvironment/>
>>>>>>>>>>>> <https://www.youtube.com/user/veoliaenvironnement>
>>>>>>>>>>>> <https://www.linkedin.com/company/veolia-environnement>
>>>>>>>>>>>> <https://twitter.com/veolia>
>>>>>>>>>>>>
>>>>>>>>>>>> On 5 June 2017 at 21:42, Eugene Kirpichov <kirpic...@google.com
>>>>>>>>>>>> > wrote:
>>>>>>>>>>>>
>>>>>>>>>>>>> Do you have a Dataflow job ID to look at?
>>>>>>>>>>>>> It might be due to fusion
>>>>>>>>>>>>> https://cloud.google.com/dataflow/service/dataflow-service-desc#preventing-fusion
>>>>>>>>>>>>>
>>>>>>>>>>>>> On Mon, Jun 5, 2017 at 12:13 PM Prabeesh K. <
>>>>>>>>>>>>> prabsma...@gmail.com> wrote:
>>>>>>>>>>>>>
>>>>>>>>>>>>>> Please try using *--worker_machine_type* n1-standard-4 or
>>>>>>>>>>>>>> n1-standard-8
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> On 5 June 2017 at 23:08, Morand, Sebastien <
>>>>>>>>>>>>>> sebastien.mor...@veolia.com> wrote:
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> I do have a problem with my tries to test scaling on
>>>>>>>>>>>>>>> dataflow.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> My dataflow is pretty simple: I get a list of files from
>>>>>>>>>>>>>>> pubsub, so the number of files I'm going to use to feed the
>>>>>>>>>>>>>>> flow is well
>>>>>>>>>>>>>>> known at the begining. Here are my steps:
>>>>>>>>>>>>>>> Let's say I have 200 files containing about 20,000,000 of
>>>>>>>>>>>>>>> records
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> - *First Step:* Read file contents from storage: files
>>>>>>>>>>>>>>> are .tar.gz containing each 4 files (CSV). I return the file
>>>>>>>>>>>>>>> content as the
>>>>>>>>>>>>>>> whole in a record
>>>>>>>>>>>>>>> *OUT:* 200 records (one for each file containing the
>>>>>>>>>>>>>>> data of all 4 files). Bascillacy it's a dict : {file1:
>>>>>>>>>>>>>>> content_of_file1,
>>>>>>>>>>>>>>> file2: content_of_file2, etc...}
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> - *Second step:* Joining the data of the 4 files in one
>>>>>>>>>>>>>>> record (the main file contains foreign key to get
>>>>>>>>>>>>>>> information from the
>>>>>>>>>>>>>>> other files)
>>>>>>>>>>>>>>> *OUT:* 20,000,000 records each for every line in the
>>>>>>>>>>>>>>> files. Each record is a list of string
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> - *Third step:* cleaning data (convert to prepare
>>>>>>>>>>>>>>> integration in bigquery) and set them as a dict where keys
>>>>>>>>>>>>>>> are bigquery
>>>>>>>>>>>>>>> column name.
>>>>>>>>>>>>>>> *OUT:* 20,000,000 records as dict for each record
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> - *Fourth step:* insert into bigquery
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> So the first step return 200 records, but I have 20,000,000
>>>>>>>>>>>>>>> records to insert.
>>>>>>>>>>>>>>> This takes about 1 hour and half and always use 1 worker ...
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> If I manually set the number of workers, it's not really
>>>>>>>>>>>>>>> faster. So for an unknow reason, it doesn't scale, any ideas
>>>>>>>>>>>>>>> how to do it?
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> Thanks for any help.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> *Sébastien MORAND*
>>>>>>>>>>>>>>> Team Lead Solution Architect
>>>>>>>>>>>>>>> Technology & Operations / Digital Factory
>>>>>>>>>>>>>>> Veolia - Group Information Systems & Technology (IS&T)
>>>>>>>>>>>>>>> Cell.: +33 7 52 66 20 81 / Direct: +33 1 85 57 71 08
>>>>>>>>>>>>>>> <+33%201%2085%2057%2071%2008>
>>>>>>>>>>>>>>> Bureau 0144C (Ouest)
>>>>>>>>>>>>>>> 30, rue Madeleine-Vionnet - 93300 Aubervilliers, France
>>>>>>>>>>>>>>> *www.veolia.com <http://www.veolia.com>*
>>>>>>>>>>>>>>> <http://www.veolia.com>
>>>>>>>>>>>>>>> <https://www.facebook.com/veoliaenvironment/>
>>>>>>>>>>>>>>> <https://www.youtube.com/user/veoliaenvironnement>
>>>>>>>>>>>>>>> <https://www.linkedin.com/company/veolia-environnement>
>>>>>>>>>>>>>>> <https://twitter.com/veolia>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
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>>>>>
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>
