Github user xiao-chen commented on a diff in the pull request:
https://github.com/apache/spark/pull/22881#discussion_r229403073
--- Diff: core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
---
@@ -471,4 +473,42 @@ object SparkHadoopUtil {
hadoopConf.set(key.substring("spark.hadoop.".length), value)
}
}
+
+
+ lazy val builderReflection: Option[(Class[_], Method, Method)] = Try {
+ val cls = Utils.classForName(
+
"org.apache.hadoop.hdfs.DistributedFileSystem$HdfsDataOutputStreamBuilder")
+ (cls, cls.getMethod("replicate"), cls.getMethod("build"))
+ }.toOption
+
+ // scalastyle:off line.size.limit
+ /**
+ * Create a path that uses replication instead of erasure coding,
regardless of the default
+ * configuration in hdfs for the given path. This can be helpful as
hdfs ec doesn't support
+ * hflush(), hsync(), or append()
+ *
https://hadoop.apache.org/docs/r3.0.0/hadoop-project-dist/hadoop-hdfs/HDFSErasureCoding.html#Limitations
+ */
+ // scalastyle:on line.size.limit
+ def createNonECFile(fs: FileSystem, path: Path): FSDataOutputStream = {
+ try {
+ // Use reflection as this uses apis only avialable in hadoop 3
+ val builderMethod = fs.getClass().getMethod("createFile",
classOf[Path])
+ val builder = builderMethod.invoke(fs, path)
+ builderReflection match {
--- End diff --
FYI - I created https://issues.apache.org/jira/browse/HDFS-14038 for hadoop
discussion.
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