Github user zsxwing commented on a diff in the pull request:
https://github.com/apache/spark/pull/3225#discussion_r20703826
--- Diff: core/src/main/scala/org/apache/spark/SparkContext.scala ---
@@ -630,7 +634,10 @@ class SparkContext(config: SparkConf) extends
SparkStatusAPI with Logging {
* necessary info (e.g. file name for a filesystem-based dataset, table
name for HyperTable),
* using the older MapReduce API (`org.apache.hadoop.mapred`).
*
- * @param conf JobConf for setting up the dataset
+ * @param conf JobConf for setting up the dataset. Note: This will be
put into a Broadcast.
--- End diff --
People may call this method directly and pass their Configuration.
```Scala
def newAPIHadoopFile[K, V, F <: NewInputFormat[K, V]](
path: String,
fClass: Class[F],
kClass: Class[K],
vClass: Class[V],
conf: Configuration = hadoopConfiguration)
```
E.g., creating a configuration for accessing hbase:
```Scala
import java.io.{DataOutputStream, ByteArrayOutputStream}
import java.lang.String
import org.apache.hadoop.hbase.client.Scan
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
import org.apache.hadoop.hbase.client.Result
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
import org.apache.hadoop.hbase.util.Base64
def convertScanToString(scan: Scan): String = {
val out: ByteArrayOutputStream = new ByteArrayOutputStream
val dos: DataOutputStream = new DataOutputStream(out)
scan.write(dos)
Base64.encodeBytes(out.toByteArray)
}
val conf = HBaseConfiguration.create()
val scan = new Scan()
scan.setCaching(500)
scan.setCacheBlocks(false)
conf.set(TableInputFormat.INPUT_TABLE, "table_name")
conf.set(TableInputFormat.SCAN, convertScanToString(scan))
val rdd = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat],
classOf[ImmutableBytesWritable], classOf[Result])
rdd.count()
```
This is fine. However, some people may need to access two tables and union
them. They may reuse the Configuration like this:
```Scala
val conf = HBaseConfiguration.create()
val scan = new Scan()
scan.setCaching(500)
scan.setCacheBlocks(false)
conf.set(TableInputFormat.INPUT_TABLE, "table_name")
conf.set(TableInputFormat.SCAN, convertScanToString(scan))
val rdd = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat],
classOf[ImmutableBytesWritable], classOf[Result])
conf.set(TableInputFormat.INPUT_TABLE, "another_table_name")
val rdd2 = sc.newAPIHadoopRDD(conf, classOf[TableInputFormat],
classOf[ImmutableBytesWritable], classOf[Result])
rdd.union(rdd2).count()
```
The result will be weird.
I think the docs should tell people not to reuse it like this.
My motivation is this mail thread:
http://apache-spark-user-list.1001560.n3.nabble.com/How-did-the-RDD-union-work-td18686.html
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