maropu commented on a change in pull request #28841: URL: https://github.com/apache/spark/pull/28841#discussion_r472578754
########## File path: sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/PathFilterSuite.scala ########## @@ -0,0 +1,501 @@ +/* + * 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.spark.sql.execution.datasources + +import java.io.File +import java.time.{LocalDateTime, ZoneOffset} +import java.time.format.DateTimeFormatter + +import org.apache.hadoop.fs.Path + +import org.apache.spark.sql.{AnalysisException, QueryTest, Row} +import org.apache.spark.sql.catalyst.util.{stringToFile, CaseInsensitiveMap, DateTimeUtils} +import org.apache.spark.sql.test.SharedSparkSession + +class PathFilterSuite extends QueryTest with SharedSparkSession { + import testImplicits._ + + test("SPARK-31962: when modifiedAfter specified with a past date") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + file.setLastModified(DateTimeUtils.currentTimestamp()) + val df = spark.read + .option("modifiedAfter", "2019-05-10T01:11:00") + .format("csv") + .load(path.toString) + assert(df.count() == 1) + } + } + + test("SPARK-31962: when modifiedBefore specified with a future date") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val df = spark.read + .option("modifiedBefore", "2090-05-10T01:11:00") + .format("csv") + .load(path.toString) + assert(df.count() == 1) + } + } + + test("SPARK-31962: when modifiedBefore specified with a past date") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + file.setLastModified(DateTimeUtils.currentTimestamp()) + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedBefore", "1984-05-01T01:00:00") + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedAfter specified with a past date, multiple files, one valid") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file1 = new File(dir, "file1.csv") + val file2 = new File(dir, "file2.csv") + stringToFile(file1, "text") + stringToFile(file2, "text") + file1.setLastModified(DateTimeUtils.currentTimestamp()) + file2.setLastModified(0) + val df = spark.read + .option("modifiedAfter", "2019-05-10T01:11:00") + .format("csv") + .load(path.toString) + assert(df.count() == 1) + } + } + + test("SPARK-31962: when modifiedAfter specified with a past date, multiple files, both valid") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file1 = new File(dir, "file1.csv") + val file2 = new File(dir, "file2.csv") + stringToFile(file1, "text") + stringToFile(file2, "text") + file1.setLastModified(DateTimeUtils.currentTimestamp()) + file2.setLastModified(DateTimeUtils.currentTimestamp()) + val df = spark.read + .option("modifiedAfter", "2019-05-10T01:11:00") + .format("csv") + .load(path.toString) + assert(df.count() == 2) + } + } + + test("SPARK-31962: when modifiedAfter specified with a past date, multiple files, none valid") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file1 = new File(dir, "file1.csv") + val file2 = new File(dir, "file2.csv") + stringToFile(file1, "text") + stringToFile(file2, "text") + file1.setLastModified(0) + file2.setLastModified(0) + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedAfter", "1984-05-01T01:00:00") + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedBefore specified with a future date, " + + "multiple files, both valid") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file1 = new File(dir, "file1.csv") + val file2 = new File(dir, "file2.csv") + stringToFile(file1, "text") + stringToFile(file2, "text") + file1.setLastModified(0) + file2.setLastModified(0) + + val time = LocalDateTime + .now() + .plusDays(3) + .format(DateTimeFormatter + .ofPattern("yyyy-MM-dd'T'HH:mm:ss")) + + val df = spark.read + .option("modifiedBefore", time) + .format("csv") + .load(path.toString) + assert(df.count() == 2) + } + } + + test("SPARK-31962: when modifiedBefore specified with a future date, multiple files, one valid") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file1 = new File(dir, "file1.csv") + val file2 = new File(dir, "file2.csv") + stringToFile(file1, "text") + stringToFile(file2, "text") + + file1.setLastModified(0) + + val failTime = + LocalDateTime.now().plusDays(3).toEpochSecond(ZoneOffset.UTC) + file2.setLastModified(failTime * 1000) + + val time = LocalDateTime + .now() + .plusHours(10) + .format(DateTimeFormatter + .ofPattern("yyyy-MM-dd'T'HH:mm:ss")) + + val df = spark.read + .option("modifiedBefore", time) + .format("csv") + .load(path.toString) + assert(df.count() == 1) + } + } + + test("SPARK-31962: when modifiedBefore specified with a future date, " + + "multiple files, none valid") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file1 = new File(dir, "file1.csv") + val file2 = new File(dir, "file2.csv") + stringToFile(file1, "text") + stringToFile(file2, "text") + + val time = LocalDateTime + .now() + .minusDays(1) + .format(DateTimeFormatter + .ofPattern("yyyy-MM-dd'T'HH:mm:ss")) + + file1.setLastModified(DateTimeUtils.currentTimestamp()) + file2.setLastModified(DateTimeUtils.currentTimestamp()) + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedBefore", time) + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedAfter specified with a past date and " + + "pathGlobalFilter returning results") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val df = spark.read + .option("modifiedAfter", "1984-05-10T01:11:00") + .option("pathGlobFilter", "*.csv") + .format("csv") + .load(path.toString) + assert(df.count() == 1) + } + } + + test("SPARK-31962: when modifiedAfter specified with past date " + + "and pathGlobFilter filtering results") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedAfter", "1984-05-01T01:00:00") + .option("pathGlobFilter", "*.txt") + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedAfter specified with future date and " + + "pathGlobFilter returning results") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedAfter", "2050-05-01T01:00:00") + .option("pathGlobFilter", "*.csv") + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedAfter specified with future date and " + + "pathGlobFilter filtering results") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedAfter", "2050-05-01T01:00:00") + .option("pathGlobFilter", "*.txt") + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedBefore and modifiedAfter are specified out of range and " + + "pathGlobFilter returning results") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedAfter", "2050-05-01T01:00:00") + .option("modifiedBefore", "2050-05-01T01:00:00") + .option("pathGlobFilter", "*.csv") + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedBefore and modifiedAfter are specified in range and " + + "pathGlobFilter returning results") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val df = spark.read + .option("modifiedAfter", "2019-05-01T01:00:00") + .option("modifiedBefore", "2025-05-01T01:00:00") + .option("pathGlobFilter", "*.csv") + .format("csv") + .load(path.toString) + assert(df.count() == 1) + } + } + + test("SPARK-31962: when modifiedBefore and modifiedAfter are specified in range and " + + "pathGlobFilter filtering results") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedAfter", "2019-05-01T01:00:00") + .option("modifiedBefore", "2025-05-01T01:00:00") + .option("pathGlobFilter", "*.txt") + .format("csv") + .load(path.toString) + }.getMessage + assert(msg.contains("Unable to infer schema for CSV")) + } + } + + test("SPARK-31962: when modifiedAfter is specified with an invalid date") { + withTempDir { dir => + val path = new Path(dir.getCanonicalPath) + val file = new File(dir, "file1.csv") + stringToFile(file, "text") + + val msg = intercept[AnalysisException] { + spark.read + .option("modifiedAfter", "2024-05+1 01:00:00") + .format("csv") + .load(path.toString) + }.getMessage + assert( + msg.contains("The timestamp provided") + && msg.contains("modifiedafter") + && msg.contains("2024-05+1 01:00:00")) + } + } + + test("SPARK-31962: PathFilterStrategies - modifiedAfter option") { + val options = CaseInsensitiveMap[String](Map("modifiedAfter" -> "2010-10-01T01:01:00")) + val strategy = PathFilterFactory.create(options) + assert(strategy.head.isInstanceOf[ModifiedAfterFilter]) + assert(strategy.size == 1) + } + + test("SPARK-31962: PathFilterStrategies - modifiedBefore option") { + val options = CaseInsensitiveMap[String](Map("modifiedBefore" -> "2020-10-01T01:01:00")) + val strategy = PathFilterFactory.create(options) + assert(strategy.head.isInstanceOf[ModifiedBeforeFilter]) + assert(strategy.size == 1) + } + + test("SPARK-31962: PathFilterStrategies - pathGlobFilter option") { + val options = CaseInsensitiveMap[String](Map("pathGlobFilter" -> "*.txt")) + val strategy = PathFilterFactory.create(options) + assert(strategy.head.isInstanceOf[PathGlobFilter]) + assert(strategy.size == 1) + } + + test("SPARK-31962: PathFilterStrategies - no options") { + val options = CaseInsensitiveMap[String](Map.empty) + val strategy = PathFilterFactory.create(options) + assert(strategy.isEmpty) + } Review comment: To separate fine-grained tests above from the end-2-end ones, could you move them into a new test suite like `PathFilterStrategySuite`? ---------------------------------------------------------------- This is an automated message from the Apache Git Service. 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