Kaya Kupferschmidt created SPARK-37290:
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Summary: Exponential planning time in case of non-deterministic
function
Key: SPARK-37290
URL: https://issues.apache.org/jira/browse/SPARK-37290
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 3.1.2
Reporter: Kaya Kupferschmidt
We are experiencing an exponential growth of processing time in case of some
DataFrame queries including non-deterministic functions. I could create a small
example program, which can be pasted into the Spark shell for reproducing the
issue:
{code:scala}
val adselect_raw = spark.createDataFrame(Seq(("imp-1",1),("imp-2",2)))
.cache()
val adselect = adselect_raw.select(
expr("uuid()").alias("userUuid"),
expr("_1").alias("impressionUuid"),
expr("_1").alias("accessDateTime"),
expr("_1").alias("publisher"),
expr("_1").alias("site"),
expr("_1").alias("placement"),
expr("_1").alias("advertiser"),
expr("_1").alias("campaign"),
expr("_1").alias("lineItem"),
expr("_1").alias("creative"),
expr("_1").alias("browserLanguage"),
expr("_1").alias("geoLocode"),
expr("_1").alias("osFamily"),
expr("_1").alias("osName"),
expr("_1").alias("browserName"),
expr("_1").alias("referrerDomain"),
expr("_1").alias("placementIabCategory"),
expr("_1").alias("placementDeviceGroup"),
expr("_1").alias("placementDevice"),
expr("_1").alias("placementVideoType"),
expr("_1").alias("placementSection"),
expr("_1").alias("placementPlayer"),
expr("_1").alias("demandType"),
expr("_1").alias("techCosts"),
expr("_1").alias("mediaCosts"),
expr("_1").alias("directSPrice"),
expr("_1").alias("network"),
expr("_1").alias("deviceSetting"),
expr("_1").alias("placementGroup"),
expr("_1").alias("postalCode"),
expr("_1").alias("householdId")
)
val adcount_raw = spark.createDataFrame(Seq(("imp-1", 1), ("imp-2", 2)))
val adcount = adcount_raw.select(
expr("_1").alias("impressionUuid"),
expr("_2").alias("accessDateTime")
)
val result = adselect.join(adcount, Seq("impressionUuid"))
result.explain()
{code}
Further reducing the program (for example by removing the join or the cache)
did not show the problem any more.
The problem occurs during planning time and debugging lead me to the function
`UnaryNode.getAllValidConstraints` where the ExpressionSet `allConstraints`
grew with an apparently exponential number of entries for the non-deterministic
function "uuid()" in the code example above. Every time a new column from the
large select is processed in the `foreach` loop in the function
`UnaryNode.getAllValidConstraints`, the number of entries for the uuid() column
in the ExpressionSet seems to be doubled.
As a workaround, we moved the uuid() column to the end of the list, which
solved the issue (since all other columns were already processed in the
`foreach` loop).
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