paleolimbot commented on code in PR #13397: URL: https://github.com/apache/arrow/pull/13397#discussion_r927204892
########## r/tests/testthat/test-compute.R: ########## @@ -0,0 +1,298 @@ +# 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. + +test_that("list_compute_functions() works", { + expect_type(list_compute_functions(), "character") + expect_true(all(!grepl("^hash_", list_compute_functions()))) +}) + + +test_that("arrow_scalar_function() works", { + # check in/out type as schema/data type + fun <- arrow_scalar_function( + function(context, x) x$cast(int64()), + schema(x = int32()), int64() + ) + expect_equal(fun$in_type[[1]], schema(x = int32())) + expect_equal(fun$out_type[[1]](), int64()) + + # check in/out type as data type/data type + fun <- arrow_scalar_function( + function(context, x) x$cast(int64()), + int32(), int64() + ) + expect_equal(fun$in_type[[1]][[1]], field("", int32())) + expect_equal(fun$out_type[[1]](), int64()) + + # check in/out type as field/data type + fun <- arrow_scalar_function( + function(context, a_name) x$cast(int64()), + field("a_name", int32()), + int64() + ) + expect_equal(fun$in_type[[1]], schema(a_name = int32())) + expect_equal(fun$out_type[[1]](), int64()) + + # check in/out type as lists + fun <- arrow_scalar_function( + function(context, x) x, + list(int32(), int64()), + list(int64(), int32()), + auto_convert = TRUE + ) + + expect_equal(fun$in_type[[1]][[1]], field("", int32())) + expect_equal(fun$in_type[[2]][[1]], field("", int64())) + expect_equal(fun$out_type[[1]](), int64()) + expect_equal(fun$out_type[[2]](), int32()) + + expect_snapshot_error(arrow_scalar_function(NULL, int32(), int32())) +}) + +test_that("arrow_scalar_function() works with auto_convert = TRUE", { + times_32_wrapper <- arrow_scalar_function( + function(context, x) x * 32, + float64(), + float64(), + auto_convert = TRUE + ) + + dummy_kernel_context <- list() + + expect_equal( + times_32_wrapper$wrapper_fun(dummy_kernel_context, list(Scalar$create(2))), + Array$create(2 * 32) + ) +}) + +test_that("register_scalar_function() adds a compute function to the registry", { + skip_if_not(CanRunWithCapturedR()) + + register_scalar_function( + "times_32", + function(context, x) x * 32.0, + int32(), float64(), + auto_convert = TRUE + ) + on.exit(unregister_binding("times_32", update_cache = TRUE)) + + expect_true("times_32" %in% names(asNamespace("arrow")$.cache$functions)) + expect_true("times_32" %in% list_compute_functions()) + + expect_equal( + call_function("times_32", Array$create(1L, int32())), + Array$create(32L, float64()) + ) + + expect_equal( + call_function("times_32", Scalar$create(1L, int32())), + Scalar$create(32L, float64()) + ) + + expect_identical( + record_batch(a = 1L) %>% + dplyr::mutate(b = times_32(a)) %>% + dplyr::collect(), + tibble::tibble(a = 1L, b = 32.0) + ) +}) + +test_that("arrow_scalar_function() with bad return type errors", { + skip_if_not(CanRunWithCapturedR()) + + register_scalar_function( + "times_32_bad_return_type_array", + function(context, x) Array$create(x, int32()), + int32(), + float64() + ) + on.exit( + unregister_binding("times_32_bad_return_type_array", update_cache = TRUE) + ) + + expect_error( + call_function("times_32_bad_return_type_array", Array$create(1L)), + "Expected return Array or Scalar with type 'double'" + ) + + register_scalar_function( + "times_32_bad_return_type_scalar", + function(context, x) Scalar$create(x, int32()), + int32(), + float64() + ) + on.exit( + unregister_binding("times_32_bad_return_type_scalar", update_cache = TRUE) + ) + + expect_error( + call_function("times_32_bad_return_type_scalar", Array$create(1L)), + "Expected return Array or Scalar with type 'double'" + ) +}) + +test_that("register_user_defined_function() can register multiple kernels", { + skip_if_not(CanRunWithCapturedR()) + + register_scalar_function( + "times_32", + function(context, x) x * 32L, + in_type = list(int32(), int64(), float64()), + out_type = function(in_types) in_types[[1]], + auto_convert = TRUE + ) + on.exit(unregister_binding("times_32", update_cache = TRUE)) + + expect_equal( + call_function("times_32", Scalar$create(1L, int32())), + Scalar$create(32L, int32()) + ) + + expect_equal( + call_function("times_32", Scalar$create(1L, int64())), + Scalar$create(32L, int64()) + ) + + expect_equal( + call_function("times_32", Scalar$create(1L, float64())), + Scalar$create(32L, float64()) + ) +}) + +test_that("register_user_defined_function() errors for unsupported specifications", { + expect_error( + register_scalar_function( + "no_kernels", + function(...) NULL, + list(), + list() + ), + "Can't register user-defined scalar function with 0 kernels" + ) + + expect_error( + register_scalar_function( + "wrong_n_args", + function(x) NULL, + int32(), + int32() + ), + "Expected `fun` to accept 2 argument\\(s\\)" + ) + + expect_error( + register_scalar_function( + "var_kernels", + function(...) NULL, + list(float64(), schema(x = float64(), y = float64())), + float64() + ), + "Kernels for user-defined function must accept the same number of arguments" + ) +}) + +test_that("user-defined functions work during multi-threaded execution", { + skip_if_not(CanRunWithCapturedR()) + skip_if_not_available("dataset") + + n_rows <- 10000 + n_partitions <- 10 + example_df <- expand.grid( + part = letters[seq_len(n_partitions)], + value = seq_len(n_rows), + stringsAsFactors = FALSE + ) + + # make sure values are different for each partition and + example_df$row_num <- seq_len(nrow(example_df)) + example_df$value <- example_df$value + match(example_df$part, letters) + + tf_dataset <- tempfile() + tf_dest <- tempfile() + on.exit(unlink(c(tf_dataset, tf_dest))) + write_dataset(example_df, tf_dataset, partitioning = "part") + + register_scalar_function( + "times_32", + function(context, x) x * 32.0, + int32(), + float64(), + auto_convert = TRUE + ) + on.exit(unregister_binding("times_32", update_cache = TRUE)) + + # check a regular collect() + result <- open_dataset(tf_dataset) %>% + dplyr::mutate(fun_result = times_32(value)) %>% + dplyr::collect() %>% + dplyr::arrange(row_num) + + expect_identical(result$fun_result, example_df$value * 32) + + # check an exec plan with head() + result <- open_dataset(tf_dataset) %>% + dplyr::mutate(fun_result = times_32(value)) %>% + head(11) %>% + dplyr::collect() + expect_equal(nrow(result), 11) + + # check a write_dataset() + open_dataset(tf_dataset) %>% + dplyr::mutate(fun_result = times_32(value)) %>% + write_dataset(tf_dest) + + result2 <- dplyr::collect(open_dataset(tf_dest)) %>% + dplyr::arrange(row_num) %>% + dplyr::collect() + + expect_identical(result2$fun_result, example_df$value * 32) +}) + +test_that("user-defined error when called from an unsupported context", { + skip_if_not_available("dataset") + skip_if_not(CanRunWithCapturedR()) + + register_scalar_function( + "times_32", + function(context, x) x * 32.0, + int32(), + float64(), + auto_convert = TRUE + ) + on.exit(unregister_binding("times_32", update_cache = TRUE)) + + stream_plan_with_udf <- function() { + rbr <- record_batch(a = 1:1000) %>% + dplyr::mutate(b = times_32(a)) %>% + as_record_batch_reader() + rbr$read_table() + } + + if (identical(tolower(Sys.info()[["sysname"]]), "windows")) { Review Comment: Nope: you're right and it's very weird. I tried to structure the test such that it either errored properly OR worked (but didn't sweep anything under the rug). To me it suggests that there's a route to conditionally evaluating on POSIX, too (I just don't know what it is yet). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: github-unsubscr...@arrow.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
