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| 1 | +/* |
| 2 | + * Licensed to the Apache Software Foundation (ASF) under one or more |
| 3 | + * contributor license agreements. See the NOTICE file distributed with |
| 4 | + * this work for additional information regarding copyright ownership. |
| 5 | + * The ASF licenses this file to You under the Apache License, Version 2.0 |
| 6 | + * (the "License"); you may not use this file except in compliance with |
| 7 | + * the License. You may obtain a copy of the License at |
| 8 | + * |
| 9 | + * http://www.apache.org/licenses/LICENSE-2.0 |
| 10 | + * |
| 11 | + * Unless required by applicable law or agreed to in writing, software |
| 12 | + * distributed under the License is distributed on an "AS IS" BASIS, |
| 13 | + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 14 | + * See the License for the specific language governing permissions and |
| 15 | + * limitations under the License. |
| 16 | + */ |
| 17 | + |
| 18 | +package org.apache.spark.sql.hive.execution |
| 19 | + |
| 20 | +import java.util.{Locale, TimeZone} |
| 21 | + |
| 22 | +import org.apache.spark.sql.hive.test.TestHive |
| 23 | +import org.apache.spark.sql.hive.test.TestHive._ |
| 24 | +import org.apache.spark.util.Utils |
| 25 | +import org.scalatest.BeforeAndAfter |
| 26 | + |
| 27 | +/** |
| 28 | + * The test suite for window functions. To actually compare results with Hive, |
| 29 | + * every test should be created by `createQueryTest`. Because we are reusing tables |
| 30 | + * for different tests and there are a few properties needed to let Hive generate golden |
| 31 | + * files, every `createQueryTest` calls should explicitly set `reset` to `false`. |
| 32 | + */ |
| 33 | +class HiveWindowFunctionQuerySuite extends HiveComparisonTest with BeforeAndAfter { |
| 34 | + private val originalTimeZone = TimeZone.getDefault |
| 35 | + private val originalLocale = Locale.getDefault |
| 36 | + private val testTempDir = Utils.createTempDir() |
| 37 | + import org.apache.spark.sql.hive.test.TestHive.implicits._ |
| 38 | + |
| 39 | + override def beforeAll() { |
| 40 | + TestHive.cacheTables = true |
| 41 | + // Timezone is fixed to America/Los_Angeles for those timezone sensitive tests (timestamp_*) |
| 42 | + TimeZone.setDefault(TimeZone.getTimeZone("America/Los_Angeles")) |
| 43 | + // Add Locale setting |
| 44 | + Locale.setDefault(Locale.US) |
| 45 | + |
| 46 | + // Create the table used in windowing.q |
| 47 | + sql("DROP TABLE IF EXISTS part") |
| 48 | + sql( |
| 49 | + """ |
| 50 | + |CREATE TABLE part( |
| 51 | + | p_partkey INT, |
| 52 | + | p_name STRING, |
| 53 | + | p_mfgr STRING, |
| 54 | + | p_brand STRING, |
| 55 | + | p_type STRING, |
| 56 | + | p_size INT, |
| 57 | + | p_container STRING, |
| 58 | + | p_retailprice DOUBLE, |
| 59 | + | p_comment STRING) |
| 60 | + """.stripMargin) |
| 61 | + val testData = TestHive.getHiveFile("data/files/part_tiny.txt").getCanonicalPath |
| 62 | + sql( |
| 63 | + s""" |
| 64 | + |LOAD DATA LOCAL INPATH '$testData' overwrite into table part |
| 65 | + """.stripMargin) |
| 66 | + // The following settings are used for generating golden files with Hive. |
| 67 | + // We have to use kryo to correctly let Hive serialize plans with window functions. |
| 68 | + // This is used to generate golden files. |
| 69 | + sql("set hive.plan.serialization.format=kryo") |
| 70 | + // Explicitly set fs to local fs. |
| 71 | + sql(s"set fs.default.name=file://$testTempDir/") |
| 72 | + //sql(s"set mapred.working.dir=${testTempDir}") |
| 73 | + // Ask Hive to run jobs in-process as a single map and reduce task. |
| 74 | + sql("set mapred.job.tracker=local") |
| 75 | + } |
| 76 | + |
| 77 | + override def afterAll() { |
| 78 | + TestHive.cacheTables = false |
| 79 | + TimeZone.setDefault(originalTimeZone) |
| 80 | + Locale.setDefault(originalLocale) |
| 81 | + TestHive.reset() |
| 82 | + } |
| 83 | + |
| 84 | + ///////////////////////////////////////////////////////////////////////////// |
| 85 | + // Tests from windowing.q |
| 86 | + ///////////////////////////////////////////////////////////////////////////// |
| 87 | + createQueryTest("windowing.q -- 1. testWindowing", |
| 88 | + s""" |
| 89 | + |select p_mfgr, p_name, p_size, |
| 90 | + |rank() over(distribute by p_mfgr sort by p_name) as r, |
| 91 | + |dense_rank() over(distribute by p_mfgr sort by p_name) as dr, |
| 92 | + |sum(p_retailprice) over |
| 93 | + |(distribute by p_mfgr sort by p_name rows between unbounded preceding and current row) as s1 |
| 94 | + |from part |
| 95 | + """.stripMargin, reset = false) |
| 96 | + |
| 97 | + createQueryTest("windowing.q -- 2. testGroupByWithPartitioning", |
| 98 | + s""" |
| 99 | + |select p_mfgr, p_name, p_size, |
| 100 | + |min(p_retailprice), |
| 101 | + |rank() over(distribute by p_mfgr sort by p_name)as r, |
| 102 | + |dense_rank() over(distribute by p_mfgr sort by p_name) as dr, |
| 103 | + |p_size, p_size - lag(p_size,1,p_size) over(distribute by p_mfgr sort by p_name) as deltaSz |
| 104 | + |from part |
| 105 | + |group by p_mfgr, p_name, p_size |
| 106 | + """.stripMargin, reset = false) |
| 107 | + |
| 108 | + createQueryTest("windowing.q -- 19. testUDAFsWithGBY", |
| 109 | + """ |
| 110 | + | |
| 111 | + |select p_mfgr,p_name, p_size, p_retailprice, |
| 112 | + |sum(p_retailprice) over w1 as s, |
| 113 | + |min(p_retailprice) as mi , |
| 114 | + |max(p_retailprice) as ma , |
| 115 | + |avg(p_retailprice) over w1 as ag |
| 116 | + |from part |
| 117 | + |group by p_mfgr,p_name, p_size, p_retailprice |
| 118 | + |window w1 as (distribute by p_mfgr sort by p_mfgr, p_name rows between 2 preceding and 2 following); |
| 119 | + | |
| 120 | + """.stripMargin, reset = false) |
| 121 | + |
| 122 | + createQueryTest("windowing.q -- 26. testGroupByHavingWithSWQAndAlias", |
| 123 | + """ |
| 124 | + |select p_mfgr, p_name, p_size, min(p_retailprice) as mi, |
| 125 | + |rank() over(distribute by p_mfgr sort by p_name) as r, |
| 126 | + |dense_rank() over(distribute by p_mfgr sort by p_name) as dr, |
| 127 | + |p_size, p_size - lag(p_size,1,p_size) over(distribute by p_mfgr sort by p_name) as deltaSz |
| 128 | + |from part |
| 129 | + |group by p_mfgr, p_name, p_size |
| 130 | + |having p_size > 0 |
| 131 | + """.stripMargin, reset = false) |
| 132 | +} |
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