title: BigQueryIO loads not offloading rows to GCS when early trigger occurs
body: <p>I'm playing around with BigQueryIO write using loads. My load trigger is set to 18 hours. I'm ingesting data from Kafka with a fixed daily window.</p>
  
  <p>Based on <a href="https://github.com/apache/beam/blob/v2.2.0/sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/BatchLoads.java#L213-L231" rel="nofollow noreferrer">https://github.com/apache/beam/blob/v2.2.0/sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/BatchLoads.java#L213-L231</a> it seems that the intended behavior is to offload rows to the filesystem when at least 500k records are in a pane</p>
  
  <p>I managed to produce ~ 600K records and waited for around 2 hours to see if the rows were uploaded to gcs, however, nothing was there. I noticed that the "GroupByDestination" step in "BatchLoads" shows 0 under "Output collections" size.</p>
  
  <p>When I use a smaller load trigger all seems fine. Shouldn't the <code>AfterPane.elementCountAtLeast(FILE_TRIGGERING_RECORD_COUNT))))</code> be triggered?</p>
  
  <p>Here is the code for writing to BigQuery</p>
  
  <pre><code>  BigQueryIO
    .writeTableRows()
    .to(new SerializableFunction[ValueInSingleWindow[TableRow], TableDestination]() {
      override def apply(input: ValueInSingleWindow[TableRow]): TableDestination = {
        val startWindow = input.getWindow.asInstanceOf[IntervalWindow].start()
        val dayPartition = DateTimeFormat.forPattern("yyyyMMdd").withZone(DateTimeZone.UTC).print(startWindow)
        new TableDestination("myproject_id:mydataset_id.table$" + dayPartition, null)
      }
    })
    .withMethod(Method.FILE_LOADS)
    .withCreateDisposition(CreateDisposition.CREATE_NEVER)
    .withWriteDisposition(WriteDisposition.WRITE_APPEND)
    .withSchema(BigQueryUtils.schemaOf[MySchema])
    .withTriggeringFrequency(Duration.standardHours(18))
    .withNumFileShards(10)
  </code></pre>
  
  <p>The job id is 2018-02-16_14_34_54-7547662103968451637. Thanks in advance.</p>