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Use spark_test_ctx fixture instead of constructing spark manually #711

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6 changes: 0 additions & 6 deletions petastorm/tests/test_copy_dataset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,18 +18,12 @@

import numpy as np
import pytest
from pyspark.sql import SparkSession
from pyspark.sql.utils import AnalysisException

from petastorm.reader import make_reader
from petastorm.tools.copy_dataset import _main, copy_dataset


@pytest.fixture()
def spark_session():
return SparkSession.builder.appName('petastorm-copy').getOrCreate()


def test_copy_and_overwrite_cli(tmpdir, synthetic_dataset):
target_url = 'file:///' + os.path.join(tmpdir.strpath, 'copied_data')
_main([synthetic_dataset.url, target_url])
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11 changes: 5 additions & 6 deletions petastorm/tests/test_dataset_metadata.py
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Expand Up @@ -13,9 +13,8 @@
# limitations under the License.

import numpy as np
import pytest
import pyarrow
from pyspark.sql import SparkSession
import pytest
from pyspark.sql.types import IntegerType

from petastorm.codecs import ScalarCodec
Expand All @@ -37,7 +36,7 @@ def test_get_schema_from_dataset_url_bogus_url():
get_schema_from_dataset_url('/invalid_url')


def test_serialize_filesystem_factory(tmpdir):
def test_serialize_filesystem_factory(tmpdir, spark_test_ctx):
SimpleSchema = Unischema('SimpleSchema', [
UnischemaField('id', np.int32, (), ScalarCodec(IntegerType()), False),
UnischemaField('foo', np.int32, (), ScalarCodec(IntegerType()), False),
Expand All @@ -50,11 +49,11 @@ def __getstate__(self):
rows_count = 10
output_url = "file://{0}/fs_factory_test".format(tmpdir)
rowgroup_size_mb = 256
spark = SparkSession.builder.config('spark.driver.memory', '2g').master('local[2]').getOrCreate()
spark = spark_test_ctx.spark
sc = spark.sparkContext
with materialize_dataset(spark, output_url, SimpleSchema, rowgroup_size_mb, filesystem_factory=BogusFS):
rows_rdd = sc.parallelize(range(rows_count))\
.map(lambda x: {'id': x, 'foo': x})\
rows_rdd = sc.parallelize(range(rows_count)) \
.map(lambda x: {'id': x, 'foo': x}) \
.map(lambda x: dict_to_spark_row(SimpleSchema, x))

spark.createDataFrame(rows_rdd, SimpleSchema.as_spark_schema()) \
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12 changes: 6 additions & 6 deletions petastorm/tests/test_end_to_end.py
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Expand Up @@ -743,13 +743,13 @@ def test_rowgroup_selector_wrong_index_name(synthetic_dataset, reader_factory):
reader_factory(synthetic_dataset.url, rowgroup_selector=SingleIndexSelector('WrongIndexName', ['some_value']))


def test_materialize_dataset_hadoop_config(tmpdir_factory):
def test_materialize_dataset_hadoop_config(tmpdir_factory, spark_test_ctx):
"""Test that using materialize_dataset does not alter the hadoop_config"""

path = tmpdir_factory.mktemp('data').strpath
tmp_url = "file://" + path
# This test does not properly check if parquet.enable.summary-metadata is restored properly with pyspark < 2.4
spark = SparkSession.builder.getOrCreate()
spark = spark_test_ctx.spark
hadoop_config = spark.sparkContext._jsc.hadoopConfiguration()

parquet_metadata_level = "COMMON_ONLY"
Expand All @@ -775,26 +775,26 @@ def test_materialize_dataset_hadoop_config(tmpdir_factory):
spark.stop()


def test_materialize_with_summary_metadata(tmpdir_factory):
def test_materialize_with_summary_metadata(tmpdir_factory, spark_test_ctx):
"""Verify _summary_metadata appears, when requested"""
path = tmpdir_factory.mktemp('data').strpath
tmp_url = "file://" + path

spark = SparkSession.builder.getOrCreate()
spark = spark_test_ctx.spark
create_test_dataset(tmp_url, range(10), spark=spark, use_summary_metadata=True)

assert os.path.exists(os.path.join(path, "_metadata"))
spark.stop()


def test_pass_in_pyarrow_filesystem_to_materialize_dataset(synthetic_dataset, tmpdir):
def test_pass_in_pyarrow_filesystem_to_materialize_dataset(synthetic_dataset, tmpdir, spark_test_ctx):
a_moved_path = tmpdir.join('moved').strpath
copytree(synthetic_dataset.path, a_moved_path)

local_fs = pyarrow.LocalFileSystem
os.remove(a_moved_path + '/_common_metadata')

spark = SparkSession.builder.getOrCreate()
spark = spark_test_ctx.spark

with materialize_dataset(spark, a_moved_path, TestSchema, filesystem_factory=local_fs):
pass
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