diff --git a/petastorm/tests/test_copy_dataset.py b/petastorm/tests/test_copy_dataset.py
index c51aef2e..f7076c1a 100644
--- a/petastorm/tests/test_copy_dataset.py
+++ b/petastorm/tests/test_copy_dataset.py
@@ -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])
diff --git a/petastorm/tests/test_dataset_metadata.py b/petastorm/tests/test_dataset_metadata.py
index fb617a67..36d848b1 100644
--- a/petastorm/tests/test_dataset_metadata.py
+++ b/petastorm/tests/test_dataset_metadata.py
@@ -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
@@ -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),
@@ -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()) \
diff --git a/petastorm/tests/test_end_to_end.py b/petastorm/tests/test_end_to_end.py
index ba68ff96..68c03d15 100644
--- a/petastorm/tests/test_end_to_end.py
+++ b/petastorm/tests/test_end_to_end.py
@@ -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"
@@ -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