My suggestion is to try to solve the problem in terms of what you want to
compute. Instead of trying to control the operational aspects like "read
all the BQ before reading Pubsub" there is presumably some reason that the
BQ data naturally "comes first", for example if its timestamps are earlier
or if there is a join or an aggregation that must include it. Whenever you
think you want to set up an operational dependency between two things that
"happen" in a pipeline, it is often best to pivot your thinking to the data
and what you are trying to compute, and the built-in dependencies will
solve the ordering problems.
So - is there a way to describe your problem in terms of the data and what
you are trying to compute?
Kenn
On Fri, Feb 24, 2023 at 10:46 AM Reuven Lax via dev <dev@beam.apache.org>
wrote:
> First PCollections are completely unordered, so there is no guarantee on
> what order you'll see events in the flattened PCollection.
>
> There may be ways to process the BigQuery data in a separate transform
> first, but it depends on the structure of the data. How large is the
> BigQuery table? Are you doing any windowed aggregations here?
>
> Reuven
>
> On Fri, Feb 24, 2023 at 10:40 AM Sahil Modak <smo...@paloaltonetworks.com>
> wrote:
>
>> Yes, this is a streaming pipeline.
>>
>> Some more details about existing implementation v/s what we want to
>> achieve.
>>
>> Current implementation:
>> Reading from pub-sub:
>>
>> Pipeline input = Pipeline.create(options);
>>
>> PCollection<String> pubsubStream = input.apply("Read From Pubsub",
>> PubsubIO.readMessagesWithAttributesAndMessageId()
>>
>> .fromSubscription(inputSubscriptionId))
>>
>>
>> Reading from bigquery:
>>
>> PCollection<String> bqStream = input.apply("Read from BQ", BigQueryIO
>> .readTableRows().fromQuery(bqQuery).usingStandardSql())
>>
>> .apply("JSon Transform", AsJsons.of(TableRow.class));
>>
>>
>> Merge the inputs:
>>
>> PCollection<String> mergedInput =
>> PCollectionList.of(pubsubStream).and(bqStream).apply("Merge Input",
>> Flatten.pCollections());
>>
>>
>>
>> Business Logic:
>>
>> mergedInput.apply("Business Logic", ParDo.of(new BusinessLogic()))
>>
>>
>>
>> Above logic is what we use currently in our pipeline.
>>
>> We want to make sure that we read from BigQuery first & pass the bqStream
>> through our BusinessLogic() before we start consuming pubsubStream.
>>
>> Is there a way to achieve this?
>>
>>
>> Thanks,
>>
>> Sahil
>>
>>
>> On Thu, Feb 23, 2023 at 10:21 PM Reuven Lax <re...@google.com> wrote:
>>
>>> Can you explain this use case some more? Is this a streaming pipeline?
>>> If so, how are you reading from BigQuery?
>>>
>>> On Thu, Feb 23, 2023 at 10:06 PM Sahil Modak via dev <
>>> dev@beam.apache.org> wrote:
>>>
>>>> Hi,
>>>>
>>>> We have a requirement wherein we are consuming input from pub/sub
>>>> (PubSubIO) as well as BQ (BQIO)
>>>>
>>>> We want to make sure that we consume the BQ stream first before we
>>>> start consuming the data from pub-sub. Is there a way to achieve this? Can
>>>> you please help with some code samples?
>>>>
>>>> Currently, we read data from big query using BigQueryIO into a
>>>> PCollection & also read data from pubsub using PubsubIO. We then use the
>>>> flatten transform in this manner.
>>>>
>>>> PCollection pubsubKvPairs = reads from pubsub using PubsubIO
>>>> PCollection bigqueryKvPairs = reads from bigquery using BigQueryIO
>>>>
>>>> kvPairs =
>>>> PCollectionList.of(pubsubKvPairs).and(bigqueryKvPairs).apply("Merge
>>>> Input", Flatten.pCollections());
>>>>
>>>>
>>>> Thanks,
>>>> Sahil
>>>>
>>>>
