def test_run_async_extract_job_submitsExtractJobAndReturnsJobIdWithProperConfig(
self, bigquery_module_patch: bigquery):
project_id = "some-project-id"
table = "some-project.some-dataset.some-table"
destination_uris = [
"gs://some-source-uri/to_object1",
"gs://some-source-uri/to_object2"
]
job_prefix = "some_job_prefix"
bigquery_module_patch.Client.return_value = self.client_mock
expected_job_id = self.JOB_ID
self.extract_job_mock = Mock(ExtractJob)
self.extract_job_mock.job_id = expected_job_id
self.client_mock.extract_table.return_value = self.extract_job_mock
ems_job_config = EmsExtractJobConfig(
compression=Compression.GZIP,
destination_format=DestinationFormat.CSV,
field_delimiter="Deli mit R",
print_header=True,
labels={"label1": "label1_value"})
ems_bigquery_client = EmsBigqueryClient(project_id, "Emelet")
result_job_id = ems_bigquery_client.run_async_extract_job(
job_id_prefix=job_prefix,
table=table,
destination_uris=destination_uris,
job_config=ems_job_config)
call_args_list = self.client_mock.extract_table.call_args_list
args = call_args_list[0][1]
assert args["location"] == "Emelet"
assert args["source"] == TableReference.from_string(table_id=table)
assert args["job_id_prefix"] == job_prefix
assert args["destination_uris"] == destination_uris
assert args["job_config"].compression == "GZIP"
assert args["job_config"].destination_format == "CSV"
assert args["job_config"].field_delimiter == "Deli mit R"
assert args["job_config"].print_header == True
assert args["job_config"].labels == {"label1": "label1_value"}
assert result_job_id == expected_job_id
class ItEmsBigqueryClient(TestCase):
ONE_DAY_IN_MS = 3600000 * 24
GCP_BIGQUERY_CLIENT = None
DATASET = None
DUMMY_QUERY = "SELECT 1 AS data"
BAD_QUERY = "VERY BAD QUERY"
INSERT_TEMPLATE = "INSERT INTO `{}` (int_data, str_data) VALUES (1, 'hello')"
SELECT_TEMPLATE = "SELECT * FROM `{}`"
DUMMY_SELECT_TO_TABLE = "SELECT 1 AS int_data, 'hello' AS str_data"
TEST_BUCKET_NAME = GCP_PROJECT_ID + "-gcp-toolkit-it"
@classmethod
def setUpClass(cls):
cls.GCP_BIGQUERY_CLIENT = bigquery.Client(GCP_PROJECT_ID,
location="EU")
cls.DATASET = cls.__dataset()
cls.__create_dataset_if_not_exists(cls.DATASET)
@classmethod
def __create_dataset_if_not_exists(cls, dataset: Dataset):
try:
cls.GCP_BIGQUERY_CLIENT.create_dataset(dataset)
except Conflict:
pass
def setUp(self):
table_name = "test_table_" + str(
int(datetime.datetime.utcnow().timestamp() * 1000))
self.test_table = self.__create_test_table(table_name,
self.DATASET.reference)
self.client = EmsBigqueryClient(GCP_PROJECT_ID)
self.storage_client = storage.Client()
def tearDown(self):
try:
bucket = self.storage_client.get_bucket(self.TEST_BUCKET_NAME)
bucket.delete(True)
except NotFound:
pass
def __create_test_table(self, table_name, dataset_id):
table_schema = [
SchemaField("int_data", "INT64"),
SchemaField("str_data", "STRING")
]
table_reference = TableReference(dataset_id, table_name)
test_table = Table(table_reference, table_schema)
test_table.time_partitioning = TimePartitioning("DAY")
self.__delete_if_exists(test_table)
self.GCP_BIGQUERY_CLIENT.create_table(test_table)
return test_table
def __get_test_bucket(self, bucket_name):
try:
bucket = self.storage_client.get_bucket(bucket_name)
except NotFound:
bucket = self.storage_client.bucket(bucket_name)
bucket.location = "europe-west1"
bucket.storage_class = "REGIONAL"
bucket.create()
return bucket
def __delete_if_exists(self, table):
try:
self.GCP_BIGQUERY_CLIENT.delete_table(table)
except NotFound:
pass
def test_run_sync_query_dummyQuery(self):
result = self.client.run_sync_query(self.DUMMY_QUERY)
rows = list(result)
assert len(rows) == 1
assert {"data": 1} == rows[0]
def test_run_sync_query_nonExistingDataset(self):
with self.assertRaises(EmsApiError) as context:
self.client.run_sync_query(
"SELECT * FROM `non_existing_dataset.whatever`")
error_message = context.exception.args[0].lower()
assert "not found" in error_message
assert GCP_PROJECT_ID in error_message
assert "non_existing_dataset" in error_message
def test_run_sync_query_onExistingData(self):
query = self.INSERT_TEMPLATE.format(self.__get_table_path())
self.client.run_sync_query(query)
query_result = self.client.run_sync_query(
self.SELECT_TEMPLATE.format(self.__get_table_path()))
assert [{"int_data": 1, "str_data": "hello"}] == list(query_result)
def test_run_sync_query_withDestinationSet(self):
ems_query_job_config = EmsQueryJobConfig(
destination_dataset=ItEmsBigqueryClient.DATASET.dataset_id,
destination_table=self.test_table.table_id)
query_with_destination_result = list(
self.client.run_sync_query(
self.DUMMY_SELECT_TO_TABLE,
ems_query_job_config=ems_query_job_config))
query_result = list(
self.client.run_sync_query(
self.SELECT_TEMPLATE.format(self.__get_table_path())))
assert [{"int_data": 1, "str_data": "hello"}] == query_result
assert query_with_destination_result == query_result
def test_run_async_query_submitsJob(self):
job_id = self.client.run_async_query(self.DUMMY_QUERY)
job = self.GCP_BIGQUERY_CLIENT.get_job(job_id)
assert job.state is not None
def test_run_get_job_list_returnsQueryJob(self):
unique_id = self.client.run_async_query(self.DUMMY_QUERY)
jobs_iterator = self.client.get_job_list()
found = unique_id in [job.job_id for job in jobs_iterator]
assert found
def test_run_get_job_list_returns2JobsIfMaxResultSetTo2(self):
for i in range(1, 3):
self.client.run_async_query(self.DUMMY_QUERY)
jobs_iterator = self.client.get_job_list(max_result=2)
assert 2 == len(list(jobs_iterator))
def test_get_jobs_with_prefix(self):
job_prefix = "testprefix" + uuid.uuid4().hex
id1 = self.client.run_async_query(self.DUMMY_QUERY,
job_id_prefix=job_prefix)
id2 = self.client.run_async_query(self.BAD_QUERY,
job_id_prefix=job_prefix)
id3 = self.client.run_async_query(self.DUMMY_QUERY,
job_id_prefix="unique_prefix")
self.__wait_for_job_submitted(id1)
self.__wait_for_job_submitted(id2)
self.__wait_for_job_submitted(id3)
min_creation_time = datetime.datetime.utcnow() - datetime.timedelta(
minutes=1)
jobs = self.client.get_jobs_with_prefix(job_prefix, min_creation_time)
job_ids = [job.job_id for job in jobs]
expected_ids = [id1, id2]
self.assertSetEqual(set(expected_ids), set(job_ids))
def test_relaunch_failed_query_jobs(self):
job_prefix = "testprefix" + uuid.uuid4().hex
id1 = self.client.run_async_query(self.DUMMY_QUERY,
job_id_prefix=job_prefix)
id2 = self.client.run_async_query(self.BAD_QUERY,
job_id_prefix=job_prefix)
id3 = self.client.run_async_query(self.BAD_QUERY,
job_id_prefix="unique_prefix")
self.__wait_for_job_submitted(id1)
self.__wait_for_job_submitted(id2)
self.__wait_for_job_submitted(id3)
min_creation_time = datetime.datetime.utcnow() - datetime.timedelta(
minutes=1)
job_ids = self.client.relaunch_failed_jobs(job_prefix,
min_creation_time)
self.assertEqual(len(job_ids), 1)
self.assertRegex(job_ids[0], job_prefix + "-retry-1-.*")
def test_relaunch_failed_extract_jobs(self):
min_creation_time = datetime.datetime.utcnow()
job_prefix = "testprefix" + uuid.uuid4().hex
bucket = self.__get_test_bucket(self.TEST_BUCKET_NAME)
blob_name = f'exported_{int(min_creation_time.timestamp())}.csv'
good_bucket = f"gs://{self.TEST_BUCKET_NAME}/{blob_name}"
wrong_bucket = f"gs://ems_not_a_god_bucket_it_test/wrong_blob.vsct"
id1 = self.client.run_async_extract_job(job_prefix,
self.__get_table_path(),
[wrong_bucket],
EmsExtractJobConfig())
id2 = self.client.run_async_extract_job(job_prefix,
self.__get_table_path(),
[good_bucket],
EmsExtractJobConfig())
id3 = self.client.run_async_extract_job("unique_prefix",
self.__get_table_path(),
[wrong_bucket],
EmsExtractJobConfig())
self.__wait_for_job_submitted(id1)
self.__wait_for_job_submitted(id2)
self.__wait_for_job_submitted(id3)
job_ids = self.client.relaunch_failed_jobs(job_prefix,
min_creation_time)
bucket.delete_blob(blob_name)
self.assertEqual(len(job_ids), 1)
self.assertRegex(job_ids[0], job_prefix + "-retry-1-.*")
def test_get_job_list_returnsLoadJob(self):
config = EmsLoadJobConfig(
{"fields": [{
"name": "some_name",
"type": "STRING"
}]},
"gs://some-non-existing-bucket-id/blob-id",
destination_project_id=GCP_PROJECT_ID,
destination_dataset="it_test_dataset",
destination_table="some_table")
min_creation_time = datetime.datetime.utcnow()
unique_id = self.client.run_async_load_job("load_job_test", config)
self.__wait_for_job_done(unique_id)
jobs_iterator = self.client.get_jobs_with_prefix(
"load_job_test", min_creation_time)
found = unique_id in [job.job_id for job in jobs_iterator]
self.assertTrue(found)
def test_get_job_list_returnsExtractJob(self):
min_creation_time = datetime.datetime.utcnow()
destination_uris = ["gs://some-non-existing-bucket-id/destination1"]
table_path = self.__get_table_path()
unique_id = self.client.run_async_extract_job(
"extract_job_test",
table_path,
destination_uris,
job_config=EmsExtractJobConfig())
self.__wait_for_job_done(unique_id)
jobs_iterator = self.client.get_jobs_with_prefix(
"extract_job_test", min_creation_time)
job: EmsExtractJob = next(j for j in jobs_iterator
if j.job_id == unique_id)
self.assertEqual(job.table, table_path)
self.assertEqual(job.destination_uris, destination_uris)
self.assertIsInstance(job.state, EmsJobState)
self.assertEqual(job.state.value, "DONE")
self.assertTrue(job.is_failed)
def test_run_async_extract_job_shouldSaveToBucket(self):
query = self.INSERT_TEMPLATE.format(self.__get_table_path())
self.client.run_sync_query(query)
min_creation_time = datetime.datetime.utcnow()
bucket_name = self.TEST_BUCKET_NAME
bucket = self.__get_test_bucket(bucket_name)
blob_name = f'exported_{int(min_creation_time.timestamp())}.csv'
job = self.__run_async_extract_job(min_creation_time, bucket_name,
blob_name, False)
blob = bucket.blob(blob_name)
self.assertFalse(job.is_failed)
self.assertTrue(blob.exists())
self.assertEqual(blob.download_as_string(), b'1,hello\n')
bucket.delete_blob(blob_name)
def test_run_async_extract_job_shouldSaveToBucketWithHeader(self):
query = self.INSERT_TEMPLATE.format(self.__get_table_path())
self.client.run_sync_query(query)
min_creation_time = datetime.datetime.utcnow()
bucket_name = self.TEST_BUCKET_NAME
bucket = self.__get_test_bucket(bucket_name)
blob_name = f'exported_{int(min_creation_time.timestamp())}.csv'
job = self.__run_async_extract_job(min_creation_time, bucket_name,
blob_name, True)
blob = bucket.blob(blob_name)
self.assertFalse(job.is_failed)
self.assertTrue(blob.exists())
self.assertEqual(blob.download_as_string(),
b'int_data,str_data\n1,hello\n')
bucket.delete_blob(blob_name)
def __run_async_extract_job(self, min_creation_time, bucket_name,
blob_name, print_header):
table_path = self.__get_table_path()
job_id_prefix = "extract_job_test"
unique_id = self.client.run_async_extract_job(
job_id_prefix, table_path, [f'gs://{bucket_name}/{blob_name}'],
EmsExtractJobConfig(compression=Compression.NONE,
destination_format=DestinationFormat.CSV,
field_delimiter=",",
print_header=print_header))
self.__wait_for_job_done(unique_id)
jobs_iterator = self.client.get_jobs_with_prefix(
job_id_prefix, min_creation_time)
job: EmsExtractJob = next(j for j in jobs_iterator
if j.job_id == unique_id)
return job
def test_get_job_list_returnsAllKindOfJobs(self):
load_config = EmsLoadJobConfig(
{"fields": [{
"name": "some_name",
"type": "STRING"
}]},
"gs://some-non-existing-bucket-id/blob-id",
destination_project_id=GCP_PROJECT_ID,
destination_dataset="it_test_dataset",
destination_table="some_table")
destination_uris = ["gs://some-non-existing-bucket-id/destination1"]
min_creation_time = datetime.datetime.utcnow()
id_for_query_job = self.client.run_async_query(self.DUMMY_QUERY,
job_id_prefix="it_job")
id_for_load_job = self.client.run_async_load_job(
job_id_prefix="it_job", config=load_config)
id_for_extract_job = self.client.run_async_extract_job(
job_id_prefix="it_job",
table=self.__get_table_path(),
destination_uris=destination_uris,
job_config=EmsExtractJobConfig(
compression=Compression.NONE,
destination_format=DestinationFormat.CSV,
field_delimiter=",",
print_header=False))
self.__wait_for_job_done(id_for_query_job)
self.__wait_for_job_done(id_for_load_job)
self.__wait_for_job_done(id_for_extract_job)
jobs_iterator = self.client.get_jobs_with_prefix(
"it_job", min_creation_time)
job_types = [type(j) for j in jobs_iterator]
self.assertEqual(3, len(job_types))
self.assertIn(EmsQueryJob, job_types)
self.assertIn(EmsLoadJob, job_types)
self.assertIn(EmsExtractJob, job_types)
def test_run_async_load_job_loadsFileFromBucketToNewBigqueryTable(self):
bucket_name = "it_test_ems_gcp_toolkit"
bucket = self.__get_test_bucket(bucket_name)
blob_name = "sample_fruit_test.csv"
blob = bucket.blob(blob_name)
random_quantity = random.randint(10000, 99000)
blob.upload_from_string(
f"apple,{random_quantity},True,1970-01-01T12:00:00.000Z\n")
source_uri = f"gs://{bucket_name}/{blob_name}"
config = EmsLoadJobConfig(
source_uri_template=source_uri,
destination_project_id=GCP_PROJECT_ID,
destination_dataset=self.DATASET.dataset_id,
destination_table="load_job_test",
schema={
"fields": [{
"type": "STRING",
"name": "fruit"
}, {
"type": "INT64",
"name": "quantity"
}, {
"type": "BOOL",
"name": "is_delicious"
}, {
"type": "TIMESTAMP",
"name": "best_before"
}]
},
write_disposition=EmsWriteDisposition.WRITE_TRUNCATE)
load_job_id = self.client.run_async_load_job("it_test", config)
self.__wait_for_job_done(load_job_id)
query = f"""
SELECT * from `{config.destination_project_id}.{config.destination_dataset}.{config.destination_table}`
"""
result = self.client.run_sync_query(query=query)
expected = [{
"fruit":
"apple",
"quantity":
random_quantity,
"is_delicious":
True,
"best_before":
datetime.datetime(1970,
1,
1,
12,
0,
0,
tzinfo=datetime.timezone.utc)
}]
self.assertEquals(expected, list(result))
def test_run_async_load_job_whenLoadingFileWithHeader_headerIsSkiped(self):
bucket_name = "it_test_ems_gcp_toolkit"
bucket = self.__get_test_bucket(bucket_name)
blob_name = "sample_test_with_header.csv"
blob = bucket.blob(blob_name)
blob.upload_from_string(f"HEADER\nROW\n")
source_uri = f"gs://{bucket_name}/{blob_name}"
config = EmsLoadJobConfig(
source_uri_template=source_uri,
destination_project_id=GCP_PROJECT_ID,
destination_dataset=self.DATASET.dataset_id,
destination_table="load_job_test_skip_header",
schema={"fields": [{
"type": "STRING",
"name": "COLUMN"
}]},
write_disposition=EmsWriteDisposition.WRITE_TRUNCATE,
skip_leading_rows=1)
load_job_id = self.client.run_async_load_job("it_test", config)
self.__wait_for_job_done(load_job_id)
query = f"""
SELECT * from `{config.destination_project_id}.{config.destination_dataset}.{config.destination_table}`
"""
result = self.client.run_sync_query(query=query)
expected = [{"COLUMN": "ROW"}]
self.assertEquals(expected, list(result))
def test_dataset_exists_WhenDatasetNotExists(self):
dataset_id = self.__generate_test_name("dataset")
self.assertFalse(self.client.dataset_exists(dataset_id))
def test_dataset_exists_WhenDatasetExists(self):
dataset_id = self.__generate_test_name("dataset")
self.client.create_dataset_if_not_exists(dataset_id)
self.assertTrue(self.client.dataset_exists(dataset_id))
self.client.delete_dataset_if_exists(dataset_id)
def test_create_dataset_if_not_exists_CreatesDataset(self):
dataset_id = self.__generate_test_name("dataset")
self.client.create_dataset_if_not_exists(dataset_id)
self.assertTrue(self.client.dataset_exists(dataset_id))
self.client.delete_dataset_if_exists(dataset_id)
def test_create_dataset_if_not_exists_DoesNotRaiseExceptionWhenAlreadyExists(
self):
dataset_id = self.__generate_test_name("dataset")
self.client.create_dataset_if_not_exists(dataset_id)
try:
self.client.create_dataset_if_not_exists(dataset_id)
except Conflict:
self.fail(
"create_dataset_if_not_exists raised AlreadyExists error")
self.client.delete_dataset_if_exists(dataset_id)
def test_delete_dataset_if_exists_WhenItIsEmpty(self):
dataset_id = self.__generate_test_name("dataset")
self.client.create_dataset_if_not_exists(dataset_id)
self.client.delete_dataset_if_exists(dataset_id)
self.assertFalse(self.client.dataset_exists(dataset_id))
def test_delete_dataset_if_exists_WhenItIsNotEmpty(self):
dataset_id = self.__generate_test_name("dataset")
table_name = self.__generate_test_name("table")
self.client.create_dataset_if_not_exists(dataset_id)
self.__create_test_table(
table_name,
Dataset(DatasetReference(GCP_PROJECT_ID, dataset_id)).reference)
self.client.delete_dataset_if_exists(dataset_id, delete_contents=True)
self.assertFalse(self.client.dataset_exists(dataset_id))
def test_delete_dataset_DoesNotRaiseExceptionWhenNotExists(self):
dataset_id = self.__generate_test_name("dataset")
try:
self.client.delete_dataset_if_exists(dataset_id)
except NotFound:
self.fail("delete_dataset_if_exists raised NotFound error")
@retry(stop=(stop_after_delay(10)))
def __wait_for_job_submitted(self, job_id):
self.GCP_BIGQUERY_CLIENT.get_job(job_id)
@retry(
stop=(stop_after_delay(10)),
retry=(
retry_if_result(lambda result: result != EmsJobState.DONE.value)))
def __wait_for_job_done(self, job_id):
return self.GCP_BIGQUERY_CLIENT.get_job(job_id).state
def __get_table_path(self):
return "{}.{}.{}".format(GCP_PROJECT_ID, self.DATASET.dataset_id,
self.test_table.table_id)
@classmethod
def __dataset(cls):
dataset = Dataset(DatasetReference(GCP_PROJECT_ID, "it_test_dataset"))
dataset.default_table_expiration_ms = cls.ONE_DAY_IN_MS
return dataset
@staticmethod
def __generate_test_name(context: str):
return "test_" + context + "_" + str(int(time.time()))