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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