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-rw-r--r--scald-mvp/src/main/scala/example/SimpleHBaseSourceExample.scala36
-rw-r--r--scald-mvp/src/main/scala/example/WordCountJob.scala12
2 files changed, 0 insertions, 48 deletions
diff --git a/scald-mvp/src/main/scala/example/SimpleHBaseSourceExample.scala b/scald-mvp/src/main/scala/example/SimpleHBaseSourceExample.scala
deleted file mode 100644
index fe2a120..0000000
--- a/scald-mvp/src/main/scala/example/SimpleHBaseSourceExample.scala
+++ /dev/null
@@ -1,36 +0,0 @@
-package example
-
-import com.twitter.scalding.{Tsv, Args}
-import parallelai.spyglass.base.JobBase
-import org.apache.log4j.{Level, Logger}
-import parallelai.spyglass.hbase.{HBasePipeConversions, HBaseSource}
-import parallelai.spyglass.hbase.HBaseConstants.SourceMode
-import cascading.tuple.Fields
-import cascading.property.AppProps
-import java.util.Properties
-
-/**
- * Simple example of HBaseSource usage
- */
-class SimpleHBaseSourceExample(args: Args) extends JobBase(args) with HBasePipeConversions {
-
- val isDebug: Boolean = args("debug").toBoolean
-
- if (isDebug) Logger.getRootLogger.setLevel(Level.DEBUG)
-
- val output = args("output")
-
- val hbs = new HBaseSource(
- "table_name",
- //"quorum_name:2181",
- "mtrcs-zk1.us.archive.org:2181", // HBase Zookeeper server (to get runtime config info; can be array?)
- new Fields("key"),
- List("column_family"),
- List(new Fields("column_name1", "column_name2")),
- sourceMode = SourceMode.GET_LIST, keyList = List("1", "2", "3"))
- .read
- .debug
- .fromBytesWritable(new Fields("key", "column_name1", "column_name2"))
- .write(Tsv(output format "get_list"))
-
- }
diff --git a/scald-mvp/src/main/scala/example/WordCountJob.scala b/scald-mvp/src/main/scala/example/WordCountJob.scala
deleted file mode 100644
index 0e63fed..0000000
--- a/scald-mvp/src/main/scala/example/WordCountJob.scala
+++ /dev/null
@@ -1,12 +0,0 @@
-package example
-
-import com.twitter.scalding._
-
-class WordCountJob(args: Args) extends Job(args) {
- TypedPipe.from(TextLine(args("input")))
- .flatMap { line => line.split("\\s+") }
- .map { word => (word, 1L) }
- .sumByKey
- // The compiler will enforce the type coming out of the sumByKey is the same as the type we have for our sink
- .write(TypedTsv[(String, Long)](args("output")))
-}