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Trim cache tests to improve integration test time [databricks] #4838

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Feb 23, 2022
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Trim cache tests to improve integration test time [databricks] #4838

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51 changes: 4 additions & 47 deletions integration_tests/src/main/python/cache_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,75 +59,32 @@ def test_passing_gpuExpr_as_Expr(enable_vectorized_conf):
BooleanGen(), DateGen(), TimestampGen()] + _cache_decimal_gens

@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
@pytest.mark.parametrize('join_type', ['Left', 'Right', 'Inner', 'LeftSemi', 'LeftAnti'], ids=idfn)
@pytest.mark.parametrize('enable_vectorized_conf', enable_vectorized_confs, ids=idfn)
@ignore_order
def test_cache_join(data_gen, join_type, enable_vectorized_conf):
def test_cache_join(data_gen, enable_vectorized_conf):
def do_join(spark):
left, right = create_df(spark, data_gen, 500, 500)
cached = left.join(right, left.a == right.r_a, join_type).cache()
cached = left.join(right, left.a == right.r_a, 'Inner').cache()
cached.count() # populates cache
return cached
assert_gpu_and_cpu_are_equal_collect(do_join, conf=enable_vectorized_conf)

@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
@pytest.mark.parametrize('join_type', ['Left', 'Right', 'Inner', 'LeftSemi', 'LeftAnti'], ids=idfn)
@pytest.mark.parametrize('enable_vectorized_conf', enable_vectorized_confs, ids=idfn)
# We are OK running everything on CPU until we complete 'https://github.com/NVIDIA/spark-rapids/issues/360'
# because we have an explicit check in our code that disallows InMemoryTableScan to have anything other than
# AttributeReference
@allow_non_gpu(any=True)
@ignore_order
def test_cached_join_filter(data_gen, join_type, enable_vectorized_conf):
def test_cached_join_filter(data_gen, enable_vectorized_conf):
data = data_gen
def do_join(spark):
left, right = create_df(spark, data, 500, 500)
cached = left.join(right, left.a == right.r_a, join_type).cache()
cached = left.join(right, left.a == right.r_a, 'Inner').cache()
cached.count() #populates the cache
return cached.filter("a is not null")
assert_gpu_and_cpu_are_equal_collect(do_join, conf=enable_vectorized_conf)

@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
@pytest.mark.parametrize('enable_vectorized_conf', enable_vectorized_confs, ids=idfn)
@pytest.mark.parametrize('join_type', ['Left', 'Right', 'Inner', 'LeftSemi', 'LeftAnti'], ids=idfn)
@ignore_order
def test_cache_broadcast_hash_join(data_gen, join_type, enable_vectorized_conf):
def do_join(spark):
left, right = create_df(spark, data_gen, 500, 500)
cached = left.join(right.hint("broadcast"), left.a == right.r_a, join_type).cache()
cached.count()
return cached

assert_gpu_and_cpu_are_equal_collect(do_join, conf=enable_vectorized_conf)

shuffled_conf = {"spark.sql.autoBroadcastJoinThreshold": "160",
"spark.sql.join.preferSortMergeJoin": "false",
"spark.sql.shuffle.partitions": "2"}

@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
@pytest.mark.parametrize('enable_vectorized_conf', enable_vectorized_confs, ids=idfn)
@pytest.mark.parametrize('join_type', ['Left', 'Right', 'Inner', 'LeftSemi', 'LeftAnti'], ids=idfn)
@ignore_order
def test_cache_shuffled_hash_join(data_gen, join_type, enable_vectorized_conf):
def do_join(spark):
left, right = create_df(spark, data_gen, 50, 500)
cached = left.join(right, left.a == right.r_a, join_type).cache()
cached.count()
return cached
assert_gpu_and_cpu_are_equal_collect(do_join, conf=enable_vectorized_conf)

@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
@pytest.mark.parametrize('enable_vectorized_conf', enable_vectorized_confs, ids=idfn)
@pytest.mark.parametrize('join_type', ['Left', 'Right', 'Inner', 'LeftSemi', 'LeftAnti'], ids=idfn)
@ignore_order
def test_cache_broadcast_nested_loop_join(data_gen, join_type, enable_vectorized_conf):
def do_join(spark):
left, right = create_df(spark, data_gen, 50, 25)
cached = left.crossJoin(right.hint("broadcast")).cache()
cached.count()
return cached
assert_gpu_and_cpu_are_equal_collect(do_join, conf=enable_vectorized_conf)

@pytest.mark.parametrize('data_gen', all_gen, ids=idfn)
@pytest.mark.parametrize('enable_vectorized_conf', enable_vectorized_confs, ids=idfn)
@ignore_order
Expand Down