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test: Add SQL file tests for left and right expressions (#3463)
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Lines changed: 123 additions & 117 deletions

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‎spark/src/test/resources/sql-tests/expressions/string/left.sql‎

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@@ -30,10 +30,37 @@ SELECT left(s, n) FROM test_str_left
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query
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SELECT left(s, 3) FROM test_str_left
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-- column + literal: edge cases
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query
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SELECT left(s, 0) FROM test_str_left
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query
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SELECT left(s, -1) FROM test_str_left
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query
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-- n exceeds length of 'hello' (5 chars)
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SELECT left(s, 10) FROM test_str_left
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-- literal + column
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query expect_fallback(Substring pos and len must be literals)
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SELECT left('hello', n) FROM test_str_left
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-- literal + literal
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query ignore(https://github.com/apache/datafusion-comet/issues/3337)
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SELECT left('hello', 3), left('hello', 0), left('hello', -1), left('', 3), left(NULL, 3)
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-- unicode
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statement
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CREATE TABLE test_str_left_unicode(s string) USING parquet
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statement
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INSERT INTO test_str_left_unicode VALUES ('café'), ('hello世界'), ('😀emoji'), ('తెలుగు'), (NULL)
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query
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SELECT s, left(s, 2) FROM test_str_left_unicode
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query
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SELECT s, left(s, 4) FROM test_str_left_unicode
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query
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SELECT s, left(s, 0) FROM test_str_left_unicode

‎spark/src/test/resources/sql-tests/expressions/string/right.sql‎

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-- Licensed to the Apache Software Foundation (ASF) under one
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-- or more contributor license agreements. See the NOTICE file
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-- distributed with this work for additional information
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-- regarding copyright ownership. The ASF licenses this file
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-- to you under the Apache License, Version 2.0 (the
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-- "License"); you may not use this file except in compliance
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-- with the License. You may obtain a copy of the License at
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--
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-- http://www.apache.org/licenses/LICENSE-2.0
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--
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-- Unless required by applicable law or agreed to in writing,
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-- software distributed under the License is distributed on an
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-- "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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-- KIND, either express or implied. See the License for the
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-- specific language governing permissions and limitations
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-- under the License.
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-- Note: Right is a RuntimeReplaceable expression. Spark replaces it with
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-- If(IsNull(str), null, If(len <= 0, "", Substring(str, -len, len)))
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-- before Comet sees it. CometRight handles the serde, but the optimizer
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-- may replace it first. We use spark_answer_only to verify correctness.
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-- ConfigMatrix: parquet.enable.dictionary=false,true
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statement
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CREATE TABLE test_str_right(s string, n int) USING parquet
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statement
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INSERT INTO test_str_right VALUES ('hello', 3), ('hello', 0), ('hello', -1), ('hello', 10), ('', 3), (NULL, 3), ('hello', NULL)
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-- both columns: len must be literal, falls back
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query spark_answer_only
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SELECT right(s, n) FROM test_str_right
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-- column + literal: basic
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query spark_answer_only
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SELECT right(s, 3) FROM test_str_right
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-- column + literal: edge cases
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query spark_answer_only
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SELECT right(s, 0) FROM test_str_right
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query spark_answer_only
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SELECT right(s, -1) FROM test_str_right
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query spark_answer_only
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-- n exceeds length of 'hello' (5 chars)
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SELECT right(s, 10) FROM test_str_right
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-- literal + column: falls back
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query spark_answer_only
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SELECT right('hello', n) FROM test_str_right
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-- literal + literal
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query spark_answer_only
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SELECT right('hello', 3), right('hello', 0), right('hello', -1), right('', 3), right(NULL, 3)
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-- null propagation with len <= 0 (critical: NULL str with non-positive len must return NULL, not empty string)
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query spark_answer_only
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SELECT right(CAST(NULL AS STRING), 0), right(CAST(NULL AS STRING), -1), right(CAST(NULL AS STRING), 2)
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-- mixed null and non-null values with len <= 0
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statement
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CREATE TABLE test_str_right_nulls(s string) USING parquet
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statement
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INSERT INTO test_str_right_nulls VALUES ('hello'), (NULL), (''), ('world')
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query spark_answer_only
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SELECT s, right(s, 0) FROM test_str_right_nulls
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query spark_answer_only
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SELECT s, right(s, -1) FROM test_str_right_nulls
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query spark_answer_only
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SELECT s, right(s, 2) FROM test_str_right_nulls
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-- equivalence with substring
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query spark_answer_only
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SELECT s, right(s, 3), substring(s, -3, 3) FROM test_str_right_nulls
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-- unicode
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statement
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CREATE TABLE test_str_right_unicode(s string) USING parquet
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statement
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INSERT INTO test_str_right_unicode VALUES ('café'), ('hello世界'), ('😀emoji'), ('తెలుగు'), (NULL)
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query spark_answer_only
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SELECT s, right(s, 2) FROM test_str_right_unicode
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query spark_answer_only
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SELECT s, right(s, 4) FROM test_str_right_unicode
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query spark_answer_only
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SELECT s, right(s, 0) FROM test_str_right_unicode

‎spark/src/test/scala/org/apache/comet/CometExpressionSuite.scala‎

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Original file line numberDiff line numberDiff line change
@@ -523,123 +523,6 @@ class CometExpressionSuite extends CometTestBase with AdaptiveSparkPlanHelper {
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}
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}
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test("LEFT function") {
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withParquetTable((0 until 10).map(i => (s"test$i", i)), "tbl") {
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 2) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 4) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 0) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, -1) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 100) FROM tbl")
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checkSparkAnswerAndOperator("SELECT LEFT(CAST(NULL AS STRING), 2) FROM tbl LIMIT 1")
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}
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}
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test("LEFT function with unicode") {
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val data = Seq("café", "hello世界", "😀emoji", "తెలుగు")
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withParquetTable(data.zipWithIndex, "unicode_tbl") {
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 2) FROM unicode_tbl")
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 3) FROM unicode_tbl")
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 0) FROM unicode_tbl")
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}
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}
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test("LEFT function equivalence with SUBSTRING") {
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withParquetTable((0 until 20).map(i => Tuple1(s"test$i")), "equiv_tbl") {
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val df = spark.sql("""
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SELECT _1,
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LEFT(_1, 3) as left_result,
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SUBSTRING(_1, 1, 3) as substring_result
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FROM equiv_tbl
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""")
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checkAnswer(
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df.filter(
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"left_result != substring_result OR " +
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"(left_result IS NULL AND substring_result IS NOT NULL) OR " +
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"(left_result IS NOT NULL AND substring_result IS NULL)"),
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Seq.empty)
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}
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}
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test("LEFT function with dictionary") {
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val data = (0 until 1000)
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.map(_ % 5)
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.map(i => s"value$i")
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withParquetTable(data.zipWithIndex, "dict_tbl") {
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checkSparkAnswerAndOperator("SELECT _1, LEFT(_1, 3) FROM dict_tbl")
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}
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}
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test("RIGHT function") {
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withParquetTable((0 until 10).map(i => (s"test$i", i)), "tbl") {
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 2) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 4) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 0) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, -1) FROM tbl")
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 100) FROM tbl")
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checkSparkAnswerAndOperator("SELECT RIGHT(CAST(NULL AS STRING), 2) FROM tbl LIMIT 1")
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}
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}
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test("RIGHT function with unicode") {
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val data = Seq("café", "hello世界", "😀emoji", "తెలుగు")
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withParquetTable(data.zipWithIndex, "unicode_tbl") {
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 2) FROM unicode_tbl")
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 3) FROM unicode_tbl")
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 0) FROM unicode_tbl")
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}
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}
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test("RIGHT function equivalence with SUBSTRING negative pos") {
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withParquetTable((0 until 20).map(i => Tuple1(s"test$i")), "equiv_tbl") {
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val df = spark.sql("""
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SELECT _1,
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RIGHT(_1, 3) as right_result,
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SUBSTRING(_1, -3, 3) as substring_result
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FROM equiv_tbl
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""")
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checkAnswer(
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df.filter(
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"right_result != substring_result OR " +
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"(right_result IS NULL AND substring_result IS NOT NULL) OR " +
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"(right_result IS NOT NULL AND substring_result IS NULL)"),
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Seq.empty)
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}
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}
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test("RIGHT function with dictionary") {
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val data = (0 until 1000)
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.map(_ % 5)
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.map(i => s"value$i")
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withParquetTable(data.zipWithIndex, "dict_tbl") {
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 3) FROM dict_tbl")
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}
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}
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test("RIGHT function NULL handling") {
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// Test NULL propagation with len = 0 (critical edge case)
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withParquetTable((0 until 5).map(i => (s"test$i", i)), "null_tbl") {
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checkSparkAnswerAndOperator("SELECT RIGHT(CAST(NULL AS STRING), 0) FROM null_tbl LIMIT 1")
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checkSparkAnswerAndOperator("SELECT RIGHT(CAST(NULL AS STRING), -1) FROM null_tbl LIMIT 1")
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checkSparkAnswerAndOperator("SELECT RIGHT(CAST(NULL AS STRING), -5) FROM null_tbl LIMIT 1")
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}
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// Test non-NULL strings with len <= 0 (should return empty string)
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withParquetTable((0 until 5).map(i => (s"test$i", i)), "edge_tbl") {
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, 0) FROM edge_tbl")
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checkSparkAnswerAndOperator("SELECT _1, RIGHT(_1, -1) FROM edge_tbl")
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}
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// Test mixed NULL and non-NULL values with a table
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val table = "right_null_edge"
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withTable(table) {
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sql(s"create table $table(str string) using parquet")
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sql(s"insert into $table values('hello'), (NULL), (''), ('world')")
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checkSparkAnswerAndOperator(s"SELECT str, RIGHT(str, 0) FROM $table")
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checkSparkAnswerAndOperator(s"SELECT str, RIGHT(str, -1) FROM $table")
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checkSparkAnswerAndOperator(s"SELECT str, RIGHT(str, 2) FROM $table")
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}
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}
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test("hour, minute, second") {
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Seq(true, false).foreach { dictionaryEnabled =>
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withTempDir { dir =>

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