LuciferYang commented on a change in pull request #30483:
URL: https://github.com/apache/spark/pull/30483#discussion_r691808961
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File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala
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@@ -967,6 +967,20 @@ object SQLConf {
.booleanConf
.createWithDefault(false)
+ val FILE_META_CACHE_PARQUET_ENABLED =
buildConf("spark.sql.fileMetaCache.parquet.enabled")
+ .doc("To indicate if enable parquet file meta cache, it is recommended to
enabled " +
Review comment:
Yes, this feature does have limitations, `NODE_LOCAL + thrift-server`
with interactive analysis should be the best scene. If the architecture is
storage and computing are separated, we need to consider the task scheduling.
In fact, [OAP](https://github.com/Intel-bigdata/OAP/tree/master/oap-cache)
project, fileMetaCache is relies on dataCache(PROCESS_LOCAL)
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