I am loading into separate partitions of the same table.
I want to see it streaming will be faster.

Is there a repository where i can use the snapshot version?


On Wed, Sep 13, 2017 at 7:19 PM, Reuven Lax <[email protected]> wrote:
> Ah, so you are loading each window into a separate BigQuery table? That
> might be the reason things are slow. Remembert a batch job doesn't return
> until everything finishes, and if you are loading that many tables it's
> entirely possible that BigQuery will throttle you, causing the slowdown.
>
> A couple of options:
>
> 1. Instead of loading into separate BigQuery tables, you could load into
> separate partitions of the same table. See this page for more info:
> https://cloud.google.com/bigquery/docs/partitioned-tables
>
> 2. If you have a streaming unbounded source for your data, you can run
> using a streaming runner. That will load each window as it becomes
> available instead of waiting for everything to load.
>
> Reuven
>
> On Tue, Sep 12, 2017 at 11:48 PM, Chaim Turkel <[email protected]> wrote:
>
>> from what i found it I have the windowing with bigquery partition (per
>> day - 1545 partitions) the insert can take 5 hours, where if there is
>> no partitions then it takes about 12 minutes
>>
>> I have 13,843,080 recrods 6.76 GB.
>> Any ideas how to get the partition to work faster.
>>
>> Is there a way to get the BigQueryIO to use streaming and not jobs?
>>
>> chaim
>>
>> On Tue, Sep 12, 2017 at 11:32 PM, Chaim Turkel <[email protected]> wrote:
>> > i am using windowing for the partion of the table, maybe that has to do
>> with it?
>> >
>> > On Tue, Sep 12, 2017 at 11:25 PM, Reuven Lax <[email protected]>
>> wrote:
>> >> Ok, something is going wrong then. It appears that your job created over
>> >> 14,000 BigQuery load jobs, which is not expected (and probably why
>> things
>> >> were so slow).
>> >>
>> >> On Tue, Sep 12, 2017 at 8:50 AM, Chaim Turkel <[email protected]> wrote:
>> >>
>> >>> no that specific job created only 2 tables
>> >>>
>> >>> On Tue, Sep 12, 2017 at 4:36 PM, Reuven Lax <[email protected]>
>> >>> wrote:
>> >>> > It looks like your job is creating about 14,45 distinct BigQuery
>> tables.
>> >>> > Does that sound correct to you?
>> >>> >
>> >>> > Reuven
>> >>> >
>> >>> > On Tue, Sep 12, 2017 at 6:22 AM, Chaim Turkel <[email protected]>
>> wrote:
>> >>> >
>> >>> >> the job id is 2017-09-12_02_57_55-5233544151932101752
>> >>> >> as you can see the majority of the time is inserting into bigquery.
>> >>> >> is there any way to parallel this?
>> >>> >>
>> >>> >> My feeling for the windowing is that writing should be done per
>> window
>> >>> >> (my window is daily) or at least to be able to configure it
>> >>> >>
>> >>> >> chaim
>> >>> >>
>> >>> >> On Tue, Sep 12, 2017 at 4:10 PM, Reuven Lax
>> <[email protected]>
>> >>> >> wrote:
>> >>> >> > So the problem is you are running on Dataflow, and it's taking
>> longer
>> >>> >> than
>> >>> >> > you think it should? If you provide the Dataflow job id we can
>> help
>> >>> you
>> >>> >> > debug why it's taking 30 minutes. (and as an aside, if this turns
>> >>> into a
>> >>> >> > Dataflow debugging session we should move it off of the Beam list
>> and
>> >>> >> onto
>> >>> >> > a Dataflow-specific tread)
>> >>> >> >
>> >>> >> > Reuven
>> >>> >> >
>> >>> >> > On Tue, Sep 12, 2017 at 3:28 AM, Chaim Turkel <[email protected]>
>> >>> wrote:
>> >>> >> >
>> >>> >> >> is there a way around this, my time for 13gb is not close to 30
>> >>> >> >> minutes, while it should be around 15 minutes.
>> >>> >> >> Do i need to chunk the code myself to windows, and run in
>> parallel?
>> >>> >> >> chaim
>> >>> >> >>
>> >>> >> >> On Sun, Sep 10, 2017 at 6:32 PM, Reuven Lax
>> <[email protected]
>> >>> >
>> >>> >> >> wrote:
>> >>> >> >> > In that case I can say unequivocally that Dataflow (in batch
>> mode)
>> >>> >> does
>> >>> >> >> not
>> >>> >> >> > produce results for a stage until it has processed that entire
>> >>> stage.
>> >>> >> The
>> >>> >> >> > reason for this is that the batch runner is optimized for
>> >>> throughput,
>> >>> >> not
>> >>> >> >> > latency; it wants to minimize the time for the entire job to
>> >>> finish,
>> >>> >> not
>> >>> >> >> > the time till first output. The side input will not be
>> materialized
>> >>> >> until
>> >>> >> >> > all of the data for all of the windows of the side input have
>> been
>> >>> >> >> > processed. The streaming runner on the other hand will produce
>> >>> >> windows as
>> >>> >> >> > they finish. So for the batch runner, there is no performance
>> >>> >> advantage
>> >>> >> >> you
>> >>> >> >> > get for windowing the side input.
>> >>> >> >> >
>> >>> >> >> > The fact that BigQueryIO needs the schema side input to be
>> globally
>> >>> >> >> > windowed is a bit confusing and not well documented. We should
>> add
>> >>> >> better
>> >>> >> >> > javadoc explaining this.
>> >>> >> >> >
>> >>> >> >> > Reuven
>> >>> >> >> >
>> >>> >> >> > On Sun, Sep 10, 2017 at 12:50 AM, Chaim Turkel <
>> [email protected]>
>> >>> >> wrote:
>> >>> >> >> >
>> >>> >> >> >> batch on dataflow
>> >>> >> >> >>
>> >>> >> >> >> On Sun, Sep 10, 2017 at 8:05 AM, Reuven Lax
>> >>> <[email protected]
>> >>> >> >
>> >>> >> >> >> wrote:
>> >>> >> >> >> > Which runner are you using? And is this a batch pipeline?
>> >>> >> >> >> >
>> >>> >> >> >> > On Sat, Sep 9, 2017 at 10:03 PM, Chaim Turkel <
>> [email protected]
>> >>> >
>> >>> >> >> wrote:
>> >>> >> >> >> >
>> >>> >> >> >> >> Thank for the answer, but i don't think that that is the
>> case.
>> >>> >> From
>> >>> >> >> >> >> what i have seen, since i have other code to update status
>> >>> based
>> >>> >> on
>> >>> >> >> >> >> the window, it does get called before all the windows are
>> >>> >> calculated.
>> >>> >> >> >> >> There is no logical reason to wait, once the window has
>> >>> finished,
>> >>> >> the
>> >>> >> >> >> >> rest of the pipeline should run and the BigQuery should
>> start
>> >>> to
>> >>> >> >> write
>> >>> >> >> >> >> the results.
>> >>> >> >> >> >>
>> >>> >> >> >> >>
>> >>> >> >> >> >>
>> >>> >> >> >> >> On Sat, Sep 9, 2017 at 10:48 PM, Reuven Lax
>> >>> >> <[email protected]
>> >>> >> >> >
>> >>> >> >> >> >> wrote:
>> >>> >> >> >> >> > Logically the BigQuery write does not depend on windows,
>> and
>> >>> >> >> writing
>> >>> >> >> >> it
>> >>> >> >> >> >> > windowed would result in incorrect output. For this
>> reason,
>> >>> >> >> BigQueryIO
>> >>> >> >> >> >> > rewindows int global windows before actually writing to
>> >>> >> BigQuery.
>> >>> >> >> >> >> >
>> >>> >> >> >> >> > If you are running in batch mode, there is no performance
>> >>> >> >> difference
>> >>> >> >> >> >> > between windowed and unwindowed side inputs. I believe
>> that
>> >>> all
>> >>> >> of
>> >>> >> >> the
>> >>> >> >> >> >> > batch runners wait until all windows are calculated
>> before
>> >>> >> >> >> materializing
>> >>> >> >> >> >> > the output.
>> >>> >> >> >> >> >
>> >>> >> >> >> >> > Reuven
>> >>> >> >> >> >> >
>> >>> >> >> >> >> > On Sat, Sep 9, 2017 at 12:43 PM, Chaim Turkel <
>> >>> [email protected]
>> >>> >> >
>> >>> >> >> >> wrote:
>> >>> >> >> >> >> >
>> >>> >> >> >> >> >> the schema depends on the data per window.
>> >>> >> >> >> >> >> when i added the global window it works, but then i
>> loose
>> >>> the
>> >>> >> >> >> >> >> performance, since the secound stage of writing will
>> begin
>> >>> only
>> >>> >> >> after
>> >>> >> >> >> >> >> the side input has read all the data and updated the
>> schema
>> >>> >> >> >> >> >> The batchmode of the BigqueryIO seems to use a global
>> window
>> >>> >> that
>> >>> >> >> i
>> >>> >> >> >> >> >> don't know why?
>> >>> >> >> >> >> >>
>> >>> >> >> >> >> >> chaim
>> >>> >> >> >> >> >>
>> >>> >> >> >> >> >> On Fri, Sep 8, 2017 at 9:26 PM, Eugene Kirpichov
>> >>> >> >> >> >> >> <[email protected]> wrote:
>> >>> >> >> >> >> >> > Are your schemas actually supposed to be different
>> between
>> >>> >> >> >> different
>> >>> >> >> >> >> >> > windows, or do they depend only on data?
>> >>> >> >> >> >> >> > I see you have a commented-out Window.into(new
>> >>> >> GlobalWindows())
>> >>> >> >> for
>> >>> >> >> >> >> your
>> >>> >> >> >> >> >> > side input - did that work when it wasn't commented
>> out?
>> >>> >> >> >> >> >> >
>> >>> >> >> >> >> >> > On Fri, Sep 8, 2017 at 2:17 AM Chaim Turkel <
>> >>> >> [email protected]>
>> >>> >> >> >> wrote:
>> >>> >> >> >> >> >> >
>> >>> >> >> >> >> >> >> my code is:
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >>                     //read docs from mongo
>> >>> >> >> >> >> >> >>                     final PCollection<Document> docs
>> =
>> >>> >> pipeline
>> >>> >> >> >> >> >> >>
>>  .apply(table.getTableName(),
>> >>> >> >> >> >> >> MongoDbIO.read()
>> >>> >> >> >> >> >> >>
>> >>>  .withUri("mongodb://" +
>> >>> >> >> >> >> >> >> connectionParams)
>> >>> >> >> >> >> >> >>
>>  .withFilter(filter)
>> >>> >> >> >> >> >> >>
>> >>>  .withDatabase(options.
>> >>> >> >> >> >> getDBName())
>> >>> >> >> >> >> >> >>
>> >>>  .withCollection(table.
>> >>> >> >> >> >> >> getTableName()))
>> >>> >> >> >> >> >> >>
>>  .apply("AddEventTimestamps",
>> >>> >> >> >> >> >> >> WithTimestamps.of((Document doc) -> new
>> >>> >> >> >> >> >> >> Instant(MongodbManagment.docTimeToLong(doc))))
>> >>> >> >> >> >> >> >>                             .apply("Window Daily",
>> >>> >> >> >> >> >> >> Window.into(CalendarWindows.days(1)));
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >>                     //update bq schema based on
>> window
>> >>> >> >> >> >> >> >>                     final PCollectionView<Map<String,
>> >>> >> String>>
>> >>> >> >> >> >> >> >> tableSchemas = docs
>> >>> >> >> >> >> >> >> //                            .apply("Global
>> >>> >> >> >> Window",Window.into(new
>> >>> >> >> >> >> >> >> GlobalWindows()))
>> >>> >> >> >> >> >> >>                             .apply("extract schema "
>> +
>> >>> >> >> >> >> >> >> table.getTableName(), new
>> >>> >> >> >> >> >> >> LoadMongodbSchemaPipeline.
>> DocsToSchemaTransform(table))
>> >>> >> >> >> >> >> >>
>>  .apply("getTableSchemaMemory
>> >>> " +
>> >>> >> >> >> >> >> >> table.getTableName(),
>> >>> >> >> >> >> >> >> ParDo.of(getTableSchemaMemory(
>> table.getTableName())))
>> >>> >> >> >> >> >> >>                             .apply(View.asMap());
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >>                     final PCollection<TableRow>
>> docsRows
>> >>> =
>> >>> >> docs
>> >>> >> >> >> >> >> >>                             .apply("doc to row " +
>> >>> >> >> >> >> >> >> table.getTableName(), ParDo.of(docToTableRow(table.
>> >>> >> >> >> getBqTableName(),
>> >>> >> >> >> >> >> >> tableSchemas))
>> >>> >> >> >> >> >> >>
>> >>> >> >>  .withSideInputs(tableSchemas))
>> >>> >> >> >> ;
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >>                     final WriteResult apply =
>> docsRows
>> >>> >> >> >> >> >> >>                             .apply("insert data
>> table -
>> >>> " +
>> >>> >> >> >> >> >> >> table.getTableName(),
>> >>> >> >> >> >> >> >>
>> >>> >>  BigQueryIO.writeTableRows()
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> .to(TableRefPartition.perDay(options.getBQProject(),
>> >>> >> >> >> >> >> >> options.getDatasetId(), table.getBqTableName()))
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> .withSchemaFromView(tableSchemas)
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> .withCreateDisposition(BigQueryIO.Write.
>> >>> >> >> >> CreateDisposition.CREATE_IF_
>> >>> >> >> >> >> >> NEEDED)
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> .withWriteDisposition(WRITE_APPEND));
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> exception is:
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> Sep 08, 2017 12:16:55 PM
>> >>> >> >> >> >> >> >> org.apache.beam.sdk.io.gcp.bigquery.TableRowWriter
>> >>> <init>
>> >>> >> >> >> >> >> >> INFO: Opening TableRowWriter to
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> gs://bq-migration/tempMongo/BigQueryWriteTemp/
>> >>> >> >> >> >> >> 7ae420d6f9eb41e488d2015d2e4d20
>> 0d/cb3f0aef-9aeb-47ac-93dc-
>> >>> >> >> >> d9a12e4fdcfb.
>> >>> >> >> >> >> >> >> Exception in thread "main"
>> >>> >> >> >> >> >> >> org.apache.beam.sdk.Pipeline$
>> PipelineExecutionException:
>> >>> >> >> >> >> >> >> java.lang.IllegalArgumentException: Attempted to get
>> >>> side
>> >>> >> >> input
>> >>> >> >> >> >> window
>> >>> >> >> >> >> >> >> for GlobalWindow from non-global WindowFn
>> >>> >> >> >> >> >> >> at
>> >>> >> >> >> >> >> >> org.apache.beam.runners.direct.DirectRunner$
>> >>> >> >> DirectPipelineResult.
>> >>> >> >> >> >> >> waitUntilFinish(DirectRunner.java:331)
>> >>> >> >> >> >> >> >> at
>> >>> >> >> >> >> >> >> org.apache.beam.runners.direct.DirectRunner$
>> >>> >> >> DirectPipelineResult.
>> >>> >> >> >> >> >> waitUntilFinish(DirectRunner.java:301)
>> >>> >> >> >> >> >> >> at org.apache.beam.runners.direct.DirectRunner.run(
>> >>> >> >> >> >> >> DirectRunner.java:200)
>> >>> >> >> >> >> >> >> at org.apache.beam.runners.direct.DirectRunner.run(
>> >>> >> >> >> >> >> DirectRunner.java:63)
>> >>> >> >> >> >> >> >> at org.apache.beam.sdk.Pipeline.
>> run(Pipeline.java:297)
>> >>> >> >> >> >> >> >> at org.apache.beam.sdk.Pipeline.
>> run(Pipeline.java:283)
>> >>> >> >> >> >> >> >> at
>> >>> >> >> >> >> >> >> com.behalf.migration.dataflow.mongodb.
>> >>> >> LoadMongodbDataPipeline.
>> >>> >> >> >> >> >> runPipeline(LoadMongodbDataPipeline.java:347)
>> >>> >> >> >> >> >> >> at
>> >>> >> >> >> >> >> >> com.behalf.migration.dataflow.mongodb.
>> >>> >> >> >> LoadMongodbDataPipeline.main(
>> >>> >> >> >> >> >> LoadMongodbDataPipeline.java:372)
>> >>> >> >> >> >> >> >> Caused by: java.lang.IllegalArgumentException:
>> >>> Attempted to
>> >>> >> >> get
>> >>> >> >> >> side
>> >>> >> >> >> >> >> >> input window for GlobalWindow from non-global
>> WindowFn
>> >>> >> >> >> >> >> >> at
>> >>> >> >> >> >> >> >> org.apache.beam.sdk.transforms.windowing.
>> >>> >> >> PartitioningWindowFn$1.
>> >>> >> >> >> >> >> getSideInputWindow(PartitioningWindowFn.java:49)
>> >>> >> >> >> >> >> >> at
>> >>> >> >> >> >> >> >> org.apache.beam.runners.direct.repackaged.runners.
>> core.
>> >>> >> >> >> >> >> SimplePushbackSideInputDoFnRunner.isReady(
>> >>> >> >> >> >> SimplePushbackSideInputDoFnRun
>> >>> >> >> >> >> >> ner.java:94)
>> >>> >> >> >> >> >> >> at
>> >>> >> >> >> >> >> >> org.apache.beam.runners.direct.repackaged.runners.
>> core.
>> >>> >> >> >> >> >> SimplePushbackSideInputDoFnRunner.
>> >>> >> processElementInReadyWindows(
>> >>> >> >> >> >> >> SimplePushbackSideInputDoFnRunner.java:76)
>> >>> >> >> >> >> >> >> Sep 08, 2017 12:16:58 PM
>> >>> >> >> >> >> >> >> org.apache.beam.sdk.io.gcp.bigquery.TableRowWriter
>> >>> <init>
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> On Thu, Sep 7, 2017 at 7:07 PM, Eugene Kirpichov
>> >>> >> >> >> >> >> >> <[email protected]> wrote:
>> >>> >> >> >> >> >> >> > Please include the full exception and please show
>> the
>> >>> code
>> >>> >> >> that
>> >>> >> >> >> >> >> produces
>> >>> >> >> >> >> >> >> it.
>> >>> >> >> >> >> >> >> > See also
>> >>> >> >> >> >> >> >> >
>> >>> >> >> >> >> >> >> https://beam.apache.org/documentation/programming-
>> >>> >> >> >> >> >> guide/#transforms-sideio
>> >>> >> >> >> >> >> >> > section
>> >>> >> >> >> >> >> >> > "Side inputs and windowing" - that might be
>> sufficient
>> >>> to
>> >>> >> >> >> resolve
>> >>> >> >> >> >> your
>> >>> >> >> >> >> >> >> > problem.
>> >>> >> >> >> >> >> >> >
>> >>> >> >> >> >> >> >> > On Thu, Sep 7, 2017 at 5:10 AM Chaim Turkel <
>> >>> >> >> [email protected]>
>> >>> >> >> >> >> wrote:
>> >>> >> >> >> >> >> >> >
>> >>> >> >> >> >> >> >> >> Hi,
>> >>> >> >> >> >> >> >> >>   I have a pipline that bases on documents from
>> mongo
>> >>> >> >> updates
>> >>> >> >> >> the
>> >>> >> >> >> >> >> >> >> schema and then adds the records to mongo. Since i
>> >>> want a
>> >>> >> >> >> >> partitioned
>> >>> >> >> >> >> >> >> >> table, i have a dally window.
>> >>> >> >> >> >> >> >> >> How do i get the schema view to be a window, i
>> get the
>> >>> >> >> >> exception
>> >>> >> >> >> >> of:
>> >>> >> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> >> Attempted to get side input window for
>> GlobalWindow
>> >>> from
>> >>> >> >> >> >> non-global
>> >>> >> >> >> >> >> >> >> WindowFn"
>> >>> >> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >> >> chaim
>> >>> >> >> >> >> >> >> >>
>> >>> >> >> >> >> >> >>
>> >>> >> >> >> >> >>
>> >>> >> >> >> >>
>> >>> >> >> >>
>> >>> >> >>
>> >>> >>
>> >>>
>>

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