fold all scorable code into sanity check; counters

1 files changed, 52 insertions, 7 deletions

diff --git a/scalding/src/main/scala/sandcrawler/GrobidScorableDumpJob.scala b/scalding/src/main/scala/sandcrawler/GrobidScorableDumpJob.scala
index 9a8d701..5e06f9b 100644
--- a/scalding/src/main/scala/sandcrawler/GrobidScorableDumpJob.scala
+++ b/scalding/src/main/scala/sandcrawler/GrobidScorableDumpJob.scala
@@ -2,17 +2,62 @@
 package sandcrawler
 
 import cascading.pipe.Pipe
-import com.twitter.scalding.Args
-import com.twitter.scalding.TypedPipe
-import com.twitter.scalding.TypedTsv
+import com.twitter.scalding._
+import com.twitter.scalding.typed.TDsl._
 import parallelai.spyglass.base.JobBase
 
+import cascading.flow.FlowDef
+import cascading.tuple.Fields
+import com.twitter.scalding._
+import com.twitter.scalding.typed.TDsl._
+import org.apache.hadoop.hbase.io.ImmutableBytesWritable
+import org.apache.hadoop.hbase.util.Bytes
+import parallelai.spyglass.hbase.HBaseConstants.SourceMode
+import parallelai.spyglass.hbase.HBasePipeConversions
+import parallelai.spyglass.hbase.HBaseSource
+
 class GrobidScorableDumpJob(args: Args) extends JobBase(args) {
 
-  val sc1 : Scorable = new GrobidScorable()
-  val pipe1 : TypedPipe[(String, ReduceFeatures)] = sc1.getInputPipe(args)
+  val grobidHbaseRows = Stat("hbase-rows-scanned", "hbase-grobid-dump")
+  val filteredGrobidRows = Stat("grobid-rows-filtered", "hbase-grobid-dump")
+  val parsedGrobidRows = Stat("grobid-rows-parsed", "hbase-grobid-dump")
+  val validGrobidRows = Stat("grobid-rows-valid-slug", "hbase-grobid-dump")
+
+  val pipe = GrobidScorable.getHBaseSource(args("hbase-table"), args("zookeeper-hosts"))
+    .read
+    // Can't just "fromBytesWritable" because we have multiple types?
+    .toTypedPipe[(ImmutableBytesWritable,ImmutableBytesWritable,ImmutableBytesWritable)](new Fields("key", "tei_json", "status_code"))
+    .filter { case (_, tei_json, status_code) =>
+      grobidHbaseRows.inc 
+      tei_json != null && status_code != null
+    }
+    .map { case (key, tei_json, status_code) =>
+      (Bytes.toString(key.copyBytes()), Bytes.toString(tei_json.copyBytes()), Bytes.toLong(status_code.copyBytes()))
+    }
+    // TODO: Should I combine next two stages for efficiency?
+    .collect { case (key, json, 200) =>
+      filteredGrobidRows.inc
+      (key, json)
+    }
+    .map { entry : (String, String) =>
+      parsedGrobidRows.inc 
+      GrobidScorable.jsonToMapFeatures(entry._1, entry._2)
+    }
+    .filter { entry => Scorable.isValidSlug(entry.slug) }
+    .map { entry => 
+      validGrobidRows.inc 
+      entry
+    }
+    // XXX: this groupBy after the map?
+    .groupBy { case MapFeatures(slug, json) => slug }
+    .map { tuple =>
+      val (slug : String, features : MapFeatures) = tuple
+      (slug, ReduceFeatures(features.json))
+    }
 
-  pipe1
-    .map { case (slug, features) => (slug, features.json) }
+  pipe
+    .map { case (slug, features) =>
+      (slug, features.json)
+    }
     .write(TypedTsv[(String, String)](args("output")))
 }