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Prevent a degenerative join in test_dpp_reuse_broadcast_exchange [databricks] #10168

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merged 8 commits into from
Jan 10, 2024
Merged

Prevent a degenerative join in test_dpp_reuse_broadcast_exchange [databricks] #10168

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dee9955
Prevent a degenerative join here so that the DPP test can correctly c…
NVnavkumar Jan 9, 2024
96fda36
Switch this to RepeatSeqGen that is shared by fact and dim tables to …
NVnavkumar Jan 9, 2024
c7e1d49
Ensure that this generates almost always positive values
NVnavkumar Jan 9, 2024
973bc1a
Use a RepeatSeqGen with a fixed sequence to ensure that join should n…
NVnavkumar Jan 9, 2024
caf274a
Address feedback
NVnavkumar Jan 9, 2024
0f5367e
2024 Copyrights
NVnavkumar Jan 9, 2024
7c7dcdb
Honor the length argument here
NVnavkumar Jan 9, 2024
16c04ea
Remove the nullable argument on RepeatSeqGen
NVnavkumar Jan 9, 2024
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9 changes: 6 additions & 3 deletions integration_tests/src/main/python/dpp_test.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
# Copyright (c) 2021-2023, NVIDIA CORPORATION.
# Copyright (c) 2021-2024, NVIDIA CORPORATION.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
Expand All @@ -20,14 +20,17 @@
from marks import ignore_order, allow_non_gpu
from spark_session import is_before_spark_320, with_cpu_session, is_before_spark_312, is_databricks_runtime, is_databricks113_or_later

# non-positive values here can produce a degenerative join, so we want a filter value associated
# with only positive values. See https://github.com/NVIDIA/spark-rapids/issues/10147
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value_gen = RepeatSeqGen(int_gen, length=100)

def create_dim_table(table_name, table_format, length=500):
def fn(spark):
df = gen_df(spark, [
('key', IntegerGen(nullable=False, min_val=0, max_val=9, special_cases=[])),
('skey', IntegerGen(nullable=False, min_val=0, max_val=4, special_cases=[])),
('ex_key', IntegerGen(nullable=False, min_val=0, max_val=3, special_cases=[])),
('value', int_gen),
('value', value_gen),
# specify nullable=False for `filter` to avoid generating invalid SQL with
# expression `filter = None` (https://github.com/NVIDIA/spark-rapids/issues/9817)
('filter', RepeatSeqGen(
Expand All @@ -49,7 +52,7 @@ def fn(spark):
('skey', IntegerGen(nullable=False, min_val=0, max_val=4, special_cases=[])),
# ex_key is not a partition column
('ex_key', IntegerGen(nullable=False, min_val=0, max_val=3, special_cases=[])),
('value', int_gen)], length)
('value', value_gen)], length)
df.write.format(table_format) \
.mode("overwrite") \
.partitionBy('key', 'skey') \
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