Talking to the BigQuery API - Google BigQuery Analytics - page 141

… else :
… print "Request %s Response %s" % (request_id,
response)
… pass

…
>>> batch.add(service.tables().get(projectId='bigquery-e2e' ,
… datasetId='application_logs' ,
… tableId='debug_20130720'), callback=batch_callback)
>>> batch.add(service.tables().get(projectId='bigquery-e2e' ,
… datasetId='application_logs' ,
… tableId='usage_logs'), callback=batch_callback)
>>> batch.execute(http=http)
Request 1 Response {
…
u'tableReference': {
u'projectId': u'bigquery-e2e',
u'tableId': u'debug_20130720',
u'datasetId': u'application_logs'},
u'numRows': u'3',
…}
Request 2 Response {
…
u'tableReference': {
u'projectId': u'bigquery-e2e',
u'tableId': u'usage_logs',
u'datasetId': u'application_logs'},
u'numRows': u'3'
…}

Before we move on, let's clean up our scratch dataset so we can start the next
section with an empty project:

$ bq rm -r -f -d scratch
$ bq rm - r - f - d scratch_2

BigQuery REST Collections

As mentioned earlier in this chapter, there are five BigQuery REST
collections: Projects, Datasets, Tables, Table Data, and Jobs. The objects