Adding range based pruning to bloom index

- keys compared lexicographically using String::compareTo
 - Range metadata additionally written into parquet file footers
 - Trim fat & few optimizations to speed up indexing
 - Add param to control whether input shall be cached, to speed up lookup
 - Add param to turn on/off range pruning
 - Auto compute of parallelism now simply factors in amount of comparisons done
 - More accurate parallelism computation when range pruning is on
 - tests added & hardened, docs updated

hoodie-client/src/main/java/com/uber/hoodie/index/bucketed/BucketedIndex.java

@@ -0,0 +1,91 @@
+/*
+ *  Copyright (c) 2017 Uber Technologies, Inc. (hoodie-dev-group@uber.com)
+ *
+ *  Licensed under the Apache License, Version 2.0 (the "License");
+ *  you may not use this file except in compliance with the License.
+ *  You may obtain a copy of the License at
+ *
+ *           http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ *
+ *
+ */
+
+package com.uber.hoodie.index.bucketed;
+
+import com.google.common.base.Optional;
+
+import com.uber.hoodie.WriteStatus;
+import com.uber.hoodie.common.model.HoodieKey;
+import com.uber.hoodie.common.model.HoodieRecord;
+import com.uber.hoodie.common.model.HoodieRecordLocation;
+import com.uber.hoodie.common.model.HoodieRecordPayload;
+import com.uber.hoodie.config.HoodieWriteConfig;
+import com.uber.hoodie.exception.HoodieIndexException;
+import com.uber.hoodie.index.HoodieIndex;
+import com.uber.hoodie.table.HoodieTable;
+
+import org.apache.log4j.LogManager;
+import org.apache.log4j.Logger;
+import org.apache.spark.api.java.JavaPairRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.apache.spark.api.java.JavaSparkContext;
+
+import scala.Tuple2;
+
+/**
+ * An `stateless` index implementation that will using a deterministic mapping function to
+ * determine the fileID for a given record.
+ *
+ * Pros:
+ *  - Fast
+ *
+ * Cons :
+ *  - Need to tune the number of buckets per partition path manually (FIXME: Need to autotune this)
+ *  - Could increase write amplification on copy-on-write storage since inserts always rewrite files
+ *  - Not global.
+ *
+ */
+public class BucketedIndex<T extends HoodieRecordPayload> extends HoodieIndex<T> {
+
+    private static Logger logger = LogManager.getLogger(BucketedIndex.class);
+
+    public BucketedIndex(HoodieWriteConfig config, JavaSparkContext jsc) {
+        super(config, jsc);
+    }
+
+    private String getBucket(String recordKey) {
+        return String.valueOf(recordKey.hashCode() % config.getNumBucketsPerPartition());
+    }
+
+    @Override
+    public JavaPairRDD<HoodieKey, Optional<String>> fetchRecordLocation(JavaRDD<HoodieKey> hoodieKeys, HoodieTable<T> table) {
+        return hoodieKeys.mapToPair(hk -> new Tuple2<>(hk, Optional.of(getBucket(hk.getRecordKey()))));
+    }
+
+    @Override
+    public JavaRDD<HoodieRecord<T>> tagLocation(JavaRDD<HoodieRecord<T>> recordRDD, HoodieTable<T> hoodieTable) throws HoodieIndexException {
+        return recordRDD.map(record -> {
+            String bucket = getBucket(record.getRecordKey());
+            //HACK(vc) a non-existent commit is provided here.
+            record.setCurrentLocation(new HoodieRecordLocation("000", bucket));
+            return record;
+        });
+    }
+
+    @Override
+    public JavaRDD<WriteStatus> updateLocation(JavaRDD<WriteStatus> writeStatusRDD, HoodieTable<T> hoodieTable) throws HoodieIndexException {
+        return writeStatusRDD;
+    }
+
+    @Override
+    public boolean rollbackCommit(String commitTime) {
+        // nothing to rollback in the index.
+        return true;
+    }
+}