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Merged
plamut merged 4 commits into from
Aug 28, 2019
Merged

BigQuery Storage: Replace obsolete test helper method #9090

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6cbd67e
Make all system tests table columns NULL-able
plamut Aug 23, 2019
74ce93d
Replace helper function with BQ client method
plamut Aug 23, 2019
05867e8
Use explicit schema in data types decoding test
plamut Aug 23, 2019
0e82bfe
Adjust a comment related to partial schemas
plamut Aug 28, 2019
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12 changes: 6 additions & 6 deletions bigquery_storage/tests/system/conftest.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,9 +69,9 @@ def table(project_id, dataset, bq_client):
from google.cloud import bigquery

schema = [
bigquery.SchemaField("first_name", "STRING", mode="REQUIRED"),
bigquery.SchemaField("first_name", "STRING", mode="NULLABLE"),
bigquery.SchemaField("last_name", "STRING", mode="NULLABLE"),
bigquery.SchemaField("age", "INTEGER", mode="REQUIRED"),
bigquery.SchemaField("age", "INTEGER", mode="NULLABLE"),
]

table_id = "{}.{}.{}".format(project_id, dataset.dataset_id, "users")
Expand Down Expand Up @@ -116,8 +116,8 @@ def col_partition_table_ref(project_id, dataset, bq_client):
from google.cloud import bigquery

schema = [
bigquery.SchemaField("occurred", "DATE", mode="REQUIRED"),
bigquery.SchemaField("description", "STRING", mode="REQUIRED"),
bigquery.SchemaField("occurred", "DATE", mode="NULLABLE"),
bigquery.SchemaField("description", "STRING", mode="NULLABLE"),
]
time_partitioning = bigquery.table.TimePartitioning(
type_=bigquery.table.TimePartitioningType.DAY, field="occurred"
Expand All @@ -144,8 +144,8 @@ def ingest_partition_table_ref(project_id, dataset, bq_client):
from google.cloud import bigquery

schema = [
bigquery.SchemaField("shape", "STRING", mode="REQUIRED"),
bigquery.SchemaField("altitude", "INT64", mode="REQUIRED"),
bigquery.SchemaField("shape", "STRING", mode="NULLABLE"),
bigquery.SchemaField("altitude", "INT64", mode="NULLABLE"),
]
time_partitioning = bigquery.table.TimePartitioning(
type_=bigquery.table.TimePartitioningType.DAY,
Expand Down
94 changes: 58 additions & 36 deletions bigquery_storage/tests/system/test_reader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,8 +18,6 @@
import copy
import datetime as dt
import decimal
import json
import io
import re

import pytest
Expand All @@ -30,42 +28,26 @@
from google.protobuf import timestamp_pb2


# TODO: remove once a similar method is implemented in the library itself
# https://github.com/googleapis/google-cloud-python/issues/4553
def _add_rows(table_ref, new_data, bq_client, partition_suffix=""):
"""Insert additional rows into an existing table.
def _to_bq_table_ref(proto_table_ref, partition_suffix=""):
"""Converts protobuf table reference to bigquery table reference.

Args:
table_ref (bigquery_storage_v1beta1.types.TableReference):
A reference to the target table.
new_data (Iterable[Dict[str, Any]]):
New data to insert with each row represented as a dictionary.
The keys must match the table column names, and the values
must be JSON serializable.
bq_client (bigquery.Client):
A BigQuery client instance to use for API calls.
proto_table_ref (bigquery_storage_v1beta1.types.TableReference):
A protobuf reference to a table.
partition_suffix (str):
An option suffix to append to the table_id, useful for selecting
An optional suffix to append to the table_id, useful for selecting
partitions of ingestion-time partitioned tables.
"""
job_config = bigquery.LoadJobConfig(
source_format=bigquery.SourceFormat.NEWLINE_DELIMITED_JSON
)

new_data_str = u"\n".join(json.dumps(item) for item in new_data)
new_data_file = io.BytesIO(new_data_str.encode())

destination_ref = bigquery.table.TableReference.from_api_repr(
Returns:
google.cloud.bigquery.table.TableReference
"""
return bigquery.table.TableReference.from_api_repr(
{
"projectId": table_ref.project_id,
"datasetId": table_ref.dataset_id,
"tableId": table_ref.table_id + partition_suffix,
"projectId": proto_table_ref.project_id,
"datasetId": proto_table_ref.dataset_id,
"tableId": proto_table_ref.table_id + partition_suffix,
}
)
job = bq_client.load_table_from_file(
new_data_file, destination=destination_ref, job_config=job_config
)
job.result() # wait for the load to complete


@pytest.mark.parametrize(
Expand Down Expand Up @@ -204,7 +186,9 @@ def test_snapshot(client, project_id, table_with_data_ref, bq_client):
{u"first_name": u"NewGuyFoo", u"last_name": u"Smith", u"age": 46},
{u"first_name": u"NewGuyBar", u"last_name": u"Jones", u"age": 30},
]
_add_rows(table_with_data_ref, new_data, bq_client)

destination = _to_bq_table_ref(table_with_data_ref)
bq_client.load_table_from_json(new_data, destination).result()

# read data using the timestamp before the additional data load
session = client.create_read_session(
Expand Down Expand Up @@ -238,7 +222,8 @@ def test_column_partitioned_table(
{"description": "1 year after false eclipse report.", "occurred": "2019-02-15"},
]

_add_rows(col_partition_table_ref, data, bq_client)
destination = _to_bq_table_ref(col_partition_table_ref)
bq_client.load_table_from_json(data, destination).result()

# Read from the table with a partition filter specified, and verify that
# only the expected data is returned.
Expand Down Expand Up @@ -279,19 +264,28 @@ def test_ingestion_time_partitioned_table(
client, project_id, ingest_partition_table_ref, bq_client, data_format
):
data = [{"shape": "cigar", "altitude": 1200}, {"shape": "disc", "altitude": 750}]
_add_rows(ingest_partition_table_ref, data, bq_client, partition_suffix="$20190809")
destination = _to_bq_table_ref(
ingest_partition_table_ref, partition_suffix="$20190809"
)
bq_client.load_table_from_json(data, destination).result()

data = [
{"shape": "sphere", "altitude": 3500},
{"shape": "doughnut", "altitude": 100},
]
_add_rows(ingest_partition_table_ref, data, bq_client, partition_suffix="$20190810")
destination = _to_bq_table_ref(
ingest_partition_table_ref, partition_suffix="$20190810"
)
bq_client.load_table_from_json(data, destination).result()

data = [
{"shape": "elephant", "altitude": 1},
{"shape": "rocket", "altitude": 12700},
]
_add_rows(ingest_partition_table_ref, data, bq_client, partition_suffix="$20190811")
destination = _to_bq_table_ref(
ingest_partition_table_ref, partition_suffix="$20190811"
)
bq_client.load_table_from_json(data, destination).result()

read_options = bigquery_storage_v1beta1.types.TableReadOptions()
read_options.row_restriction = "DATE(_PARTITIONTIME) = '2019-08-10'"
Expand Down Expand Up @@ -345,7 +339,35 @@ def test_decoding_data_types(
}
]

_add_rows(all_types_table_ref, data, bq_client)
# Explicit schema is needed to recognize bytes_field as BYTES, and not STRING.
# Since partial schemas are not supported in load_table_from_json(), a full
# schema needs to be specified.
schema = [
bigquery.SchemaField("string_field", "STRING"),
bigquery.SchemaField("bytes_field", "BYTES"),
bigquery.SchemaField("int64_field", "INT64"),
bigquery.SchemaField("float64_field", "FLOAT64"),
bigquery.SchemaField("numeric_field", "NUMERIC"),
bigquery.SchemaField("bool_field", "BOOL"),
bigquery.SchemaField("geography_field", "GEOGRAPHY"),
bigquery.SchemaField(
"person_struct_field",
"STRUCT",
fields=(
bigquery.SchemaField("name", "STRING"),
bigquery.SchemaField("age", "INT64"),
),
),
bigquery.SchemaField("timestamp_field", "TIMESTAMP"),
bigquery.SchemaField("date_field", "DATE"),
bigquery.SchemaField("time_field", "TIME"),
bigquery.SchemaField("datetime_field", "DATETIME"),
bigquery.SchemaField("string_array_field", "STRING", mode="REPEATED"),
]

job_config = bigquery.LoadJobConfig(schema=schema)
destination = _to_bq_table_ref(all_types_table_ref)
bq_client.load_table_from_json(data, destination, job_config=job_config).result()

session = client.create_read_session(
all_types_table_ref,
Expand Down