Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18216
OK, I tried this as a test:
```
import scala.collection.JavaConverters._
spark.sql("DROP TABLE IF EXISTS my_tab")
spark.sql("CREATE TABLE my_tab(a INT, b STRING, c INT, d String) USING
parquet PARTITIONED BY (a, b, c)")
spark.sql("INSERT INTO TABLE my_tab VALUES (1, 'foo', 4, 'bing')")
spark.sql("INSERT INTO TABLE my_tab VALUES (2, 'bar', 5, 'bing')")
spark.sql("INSERT INTO TABLE my_tab VALUES (3, 'baz', 6, 'bing')")
Thread.getAllStackTraces.keySet().asScala.map(_.getName).filter(_.contains("ForkJoinPool"))
res5: scala.collection.mutable.Set[String] = Set(ForkJoinPool-1-worker-13)
spark.sql("ALTER TABLE my_tab RECOVER PARTITIONS")
Thread.getAllStackTraces.keySet().asScala.map(_.getName).filter(_.contains("ForkJoinPool"))
res10: scala.collection.mutable.Set[String] = Set(ForkJoinPool-1-worker-13,
ForkJoinPool-1-worker-9, ForkJoinPool-2-worker-13)
spark.sql("ALTER TABLE my_tab RECOVER PARTITIONS")
spark.sql("ALTER TABLE my_tab RECOVER PARTITIONS")
spark.sql("ALTER TABLE my_tab RECOVER PARTITIONS")
res23: scala.collection.mutable.Set[String] = Set(ForkJoinPool-5-worker-13,
ForkJoinPool-3-worker-13, ForkJoinPool-2-worker-13, ForkJoinPool-1-worker-11,
ForkJoinPool-4-worker-13, ForkJoinPool-1-worker-3)
```
Before the change you can see that it does look like one thread is left
from each of several ForkJoinPools.
After the change, the result is `Set(ForkJoinPool-1-worker-13)` every time.
I think that does suggest this fixes the issue.
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