Github user manishgupta88 commented on a diff in the pull request:
https://github.com/apache/carbondata/pull/1670#discussion_r157947459
--- Diff:
examples/spark2/src/main/scala/org/apache/carbondata/examples/ConcurrencyTest.scala
---
@@ -0,0 +1,355 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You 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 org.apache.carbondata.examples
+
+import java.io.File
+import java.util
+import java.util.concurrent.{Callable, Executors, Future, TimeUnit}
+
+import scala.util.Random
+
+import org.apache.spark.sql.{DataFrame, Row, SaveMode, SparkSession}
+import org.apache.spark.sql.types._
+
+import org.apache.carbondata.core.constants.CarbonCommonConstants
+import org.apache.carbondata.core.util.CarbonProperties
+
+// scalastyle:off println
+object ConcurrencyTest {
+
+ var totalNum = 100 * 1000 * 1000
+ var ThreadNum = 16
+ var TaskNum = 100
+ var ResultIsEmpty = true
+ val cardinalityId = 10000 * 10000
+ val cardinalityCity = 6
+
+ def parquetTableName: String = "comparetest_parquet"
+
+ def orcTableName: String = "comparetest_orc"
+
+ def carbonTableName(version: String): String =
s"comparetest_carbonV$version"
+
+ // Table schema:
+ // +-------------+-----------+-------------+-------------+------------+
+ // | id | string | 100,000,000 | dimension | no |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | Column name | Data type | Cardinality | Column type | Dictionary |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | city | string | 6 | dimension | yes |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | country | string | 6 | dimension | yes |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | planet | string | 100,007 | dimension | yes |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | m1 | short | NA | measure | no |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | m2 | int | NA | measure | no |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | m3 | big int | NA | measure | no |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | m4 | double | NA | measure | no |
+ // +-------------+-----------+-------------+-------------+------------+
+ // | m5 | decimal | NA | measure | no |
+ // +-------------+-----------+-------------+-------------+------------+
+
+ private def generateDataFrame(spark: SparkSession): DataFrame = {
+ val rdd = spark.sparkContext
+ .parallelize(1 to totalNum, 4)
+ .map { x =>
+ ((x % 100000000).toString, "city" + x % 6, "country" + x % 6,
"planet" + x % 10007,
+ (x % 16).toShort, x / 2, (x << 1).toLong, x.toDouble / 13,
+ BigDecimal.valueOf(x.toDouble / 11))
+ }.map { x =>
+ Row(x._1, x._2, x._3, x._4, x._5, x._6, x._7, x._8, x._9)
+ }
+
+ val schema = StructType(
+ Seq(
+ StructField("id", StringType, nullable = false),
+ StructField("city", StringType, nullable = false),
+ StructField("country", StringType, nullable = false),
+ StructField("planet", StringType, nullable = false),
+ StructField("m1", ShortType, nullable = false),
+ StructField("m2", IntegerType, nullable = false),
+ StructField("m3", LongType, nullable = false),
+ StructField("m4", DoubleType, nullable = false),
+ StructField("m5", DecimalType(30, 10), nullable = false)
+ )
+ )
+
+ spark.createDataFrame(rdd, schema)
+ }
+
+ // performance test queries, they are designed to test various data
access type
+ val r = new Random()
+ val tmpId = r.nextInt(cardinalityId) % totalNum
+ val tmpCity = "city" + (r.nextInt(cardinalityCity) % totalNum)
+ val queries: Array[Query] = Array(
--- End diff --
I think it is better to give an option to read queries, table name and
database name from external file...so that any number of queries can be added
without modifying the code.....This will also help to standalone run this class
and specifying the query file path as an argument to it.
If not now, you can enhance the framework in another PR
---
