/* * 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.mozilla.spark.sql.hyperloglog.test import com.mozilla.spark.sql.hyperloglog.aggregates._ import com.mozilla.spark.sql.hyperloglog.functions._ import org.apache.spark.sql.SQLContext import org.apache.spark.sql.functions._ import org.apache.spark.{SparkConf, SparkContext} import org.scalatest.{FlatSpec, Matchers} class HyperLogLogTest extends FlatSpec with Matchers{ "Algebird's HyperLogLog" can "be used from Spark" in { val sparkConf = new SparkConf().setAppName("HyperLogLog") sparkConf.setMaster(sparkConf.get("spark.master", "local[1]")) val sc = new SparkContext(sparkConf) val sqlContext = new SQLContext(sc) import sqlContext.implicits._ val hllMerge = new HyperLogLogMerge sqlContext.udf.register("hll_merge", hllMerge) sqlContext.udf.register("hll_create", hllCreate _) sqlContext.udf.register("hll_cardinality", hllCardinality _) val frame = sc.parallelize(List("a", "b", "c", "c"), 4).toDF("id") val count = frame .select(expr("hll_create(id, 12) as hll")) .groupBy() .agg(expr("hll_cardinality(hll_merge(hll)) as count")) .collect() count(0)(0) should be (3) } }