I'm trying to build a Streaming Dataflow Job which read events from Pub/Sub and write them into BigQuery.
According to the documentation, Dataflow can detect duplicate messages delivery if a Record ID is used (see: https://cloud.google.com/dataflow/model/pubsub-io#using-record-ids)
But even using this Record ID, I still have some duplicates (around 0.0002%).
Did I miss something ?
EDIT:
I use Spotify Async PubSub Client to publish messages with the following snipplet:
Message
.builder()
.data(new String(Base64.encodeBase64(json.getBytes())))
.attributes("myid", id, "mytimestamp", timestamp.toString)
.build()
Then I use Spotify scio to read the message from pub/sub and save it to DataFlow:
val input = sc.withName("ReadFromSubscription")
.pubsubSubscription(subscriptionName, "myid", "mytimestamp")
input
.withName("FixedWindow")
.withFixedWindows(windowSize) // apply windowing logic
.toWindowed // convert to WindowedSCollection
//
.withName("ParseJson")
.map { wv =>
wv.copy(value = TableRow(
"message_id" -> (Json.parse(wv.value) \ "id").as[String],
"message" -> wv.value)
)
}
//
.toSCollection // convert back to normal SCollection
//
.withName("SaveToBigQuery")
.saveAsBigQuery(bigQueryTable(opts), BQ_SCHEMA, WriteDisposition.WRITE_APPEND)
The Window size is 1 minute.
After only few seconds injecting messages I already have duplicates in BigQuery.
I use this query to count duplicates:
SELECT
COUNT(message_id) AS TOTAL,
COUNT(DISTINCT message_id) AS DISTINCT_TOTAL
FROM my_dataset.my_table
//returning 273666 273564
And this one to look at them:
SELECT *
FROM my_dataset.my_table
WHERE message_id IN (
SELECT message_id
FROM my_dataset.my_table
GROUP BY message_id
HAVING COUNT(*) > 1
) ORDER BY message_id
//returning for instance:
row|id | processed_at | processed_at_epoch
1 00166a5c-9143-3b9e-92c6-aab52601b0be 2017-02-02 14:06:50 UTC 1486044410367 { ...json1... }
2 00166a5c-9143-3b9e-92c6-aab52601b0be 2017-02-02 14:06:50 UTC 1486044410368 { ...json1... }
3 00354cc4-4794-3878-8762-f8784187c843 2017-02-02 13:59:33 UTC 1486043973907 { ...json2... }
4 00354cc4-4794-3878-8762-f8784187c843 2017-02-02 13:59:33 UTC 1486043973741 { ...json2... }
5 0047284e-0e89-3d57-b04d-ebe4c673cc1a 2017-02-02 14:09:10 UTC 1486044550489 { ...json3... }
6 0047284e-0e89-3d57-b04d-ebe4c673cc1a 2017-02-02 14:08:52 UTC 1486044532680 { ...json3... }