# # 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. # library(testthat) context("MLlib statistics algorithms") # Tests for MLlib statistics algorithms in SparkR sparkSession <- sparkR.session(enableHiveSupport = FALSE) test_that("spark.kstest", { data <- data.frame(test = c(0.1, 0.15, 0.2, 0.3, 0.25, -1, -0.5)) df <- createDataFrame(data) testResult <- spark.kstest(df, "test", "norm") stats <- summary(testResult) rStats <- ks.test(data$test, "pnorm", alternative = "two.sided") expect_equal(stats$p.value, rStats$p.value, tolerance = 1e-4) expect_equal(stats$statistic, unname(rStats$statistic), tolerance = 1e-4) expect_match(capture.output(stats)[1], "Kolmogorov-Smirnov test summary:") testResult <- spark.kstest(df, "test", "norm", -0.5) stats <- summary(testResult) rStats <- ks.test(data$test, "pnorm", -0.5, 1, alternative = "two.sided") expect_equal(stats$p.value, rStats$p.value, tolerance = 1e-4) expect_equal(stats$statistic, unname(rStats$statistic), tolerance = 1e-4) expect_match(capture.output(stats)[1], "Kolmogorov-Smirnov test summary:") # Test print.summary.KSTest printStats <- capture.output(print.summary.KSTest(stats)) expect_match(printStats[1], "Kolmogorov-Smirnov test summary:") expect_match(printStats[5], "Low presumption against null hypothesis: Sample follows theoretical distribution. ") }) sparkR.session.stop()