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Original file line number Diff line number Diff line change
@@ -0,0 +1,113 @@
/*
* 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

class AuronInstrSuite extends QueryTest with SparkQueryTestsBase {

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This suite looks like it may not contribute any coverage today, and I want to flag the mechanism since it reads as if its asserts run. AuronInstrSuite extends QueryTest with SparkQueryTestsBase. SparkTestsBase overrides test() to route to super.ignore() whenever shouldRun(testName) is false (SparkTestsBase.scala:98-105), and shouldRun delegates to SparkTestSettings.shouldRun(...), which returns false for any suite not registered via enableSuite[...] in AuronSparkTestSettings (SparkTestSettings.scala:45-47). This suite isn't registered there (grep -rn AuronInstrSuite auron-spark-tests/ finds nothing) — that enableSuite harness is for running Spark's own upstream suites (e.g. AuronStringFunctionsSuite extends StringFunctionsSuite). The effect is that all six test() blocks become ignore(), so the hard-coded asserts like rows(0).getInt(0) == 7 never execute. Is that the intent, or were these meant to run?

Two of the tests are also weak even if they did run: "in group by" (:86-98) asserts only result.length >= 1 and the query never calls instr at all, and "in where clause" (:100-112) asserts only result.length >= 1, which is near-tautological. Separately, the manual asserts only check the answer, not that the native operator actually ran — whereas AuronFunctionSuite uses checkSparkAnswerAndOperator, which verifies both Spark parity and native-operator execution (the repo's canonical convention). Given all that, would folding the instr coverage into AuronFunctionSuite and dropping this suite be the cleaner path? That would also make the empty-substring behavior I asked about on spark_instr.rs land on a test that genuinely runs.


test("test instr function - basic functionality") {
val data = Seq(
("hello world", "world"),
("hello world", "hello"),
("hello world", "o"),
("hello world", "z"),
(null, "test"),
("test", null))

val df = spark.createDataFrame(data).toDF("str", "substr")
val rows = df.selectExpr("instr(str, substr)").collect()

// Check non-null results
assert(rows(0).getInt(0) == 7, "instr('hello world', 'world') should return 7")
assert(rows(1).getInt(0) == 1, "instr('hello world', 'hello') should return 1")
assert(rows(2).getInt(0) == 5, "instr('hello world', 'o') should return 5")
assert(rows(3).getInt(0) == 0, "instr('hello world', 'z') should return 0")

// Check null results
assert(rows(4).isNullAt(0), "instr(null, 'test') should return null")
assert(rows(5).isNullAt(0), "instr('test', null) should return null")
}

test("test instr function - multiple occurrences") {
val data = Seq(("banana", "a"), ("testtesttest", "test"), ("abcabcabc", "abc"))

val df = spark.createDataFrame(data).toDF("str", "substr")
val result = df.selectExpr("instr(str, substr)").collect().map(_.getInt(0))

assert(result(0) == 2, "instr('banana', 'a') should return 2")
assert(result(1) == 1, "instr('testtesttest', 'test') should return 1")
assert(result(2) == 1, "instr('abcabcabc', 'abc') should return 1")
}

test("test instr function - case sensitive") {
val data = Seq(("Hello", "hello"), ("HELLO", "hello"), ("Hello", "Hello"), ("hElLo", "hello"))

val df = spark.createDataFrame(data).toDF("str", "substr")
val result = df.selectExpr("instr(str, substr)").collect().map(_.getInt(0))

assert(result(0) == 0, "instr('Hello', 'hello') should return 0 (case sensitive)")
assert(result(1) == 0, "instr('HELLO', 'hello') should return 0 (case sensitive)")
assert(result(2) == 1, "instr('Hello', 'Hello') should return 1")
assert(result(3) == 0, "instr('hElLo', 'hello') should return 0 (case sensitive)")
}

test("test instr function - with filter") {
val data = Seq(
("hello world", "world", 1),
("hello", "world", 0),
("hello", "hello", 1),
("test", "abc", 0))

val df = spark.createDataFrame(data).toDF("str", "substr", "expected")
val result = df
.filter("instr(str, substr) > 0")
.select("str")
.collect()
.map(_.getString(0))

assert(result.length == 2, "Should find 2 matching strings")
assert(result.contains("hello world"))
assert(result.contains("hello"))
}

test("test instr function - in group by") {
val data = Seq(("test1", "test"), ("test2", "test"), ("hello", "world"), ("testing", "test"))

val df = spark.createDataFrame(data).toDF("str", "substr")
val result = df
.groupBy("substr")
.count()
.filter("count > 0")
.orderBy("substr")
.collect()

assert(result.length >= 1)
Comment on lines +90 to +97

Copilot AI Mar 12, 2026

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This test is titled "in group by" but it never evaluates instr (it only groups by substr and counts). As written, it doesn't validate that instr works correctly in the presence of aggregations / grouping. Consider incorporating instr(...) either in the grouping key, an aggregate expression, or a post-aggregation filter so the test actually exercises the new function in a group-by context.

Suggested change
val result = df
.groupBy("substr")
.count()
.filter("count > 0")
.orderBy("substr")
.collect()
assert(result.length >= 1)
df.createOrReplaceTempView("instr_group_test")
val result = spark.sql(
"""
|SELECT
| substr,
| SUM(CASE WHEN instr(str, substr) > 0 THEN 1 ELSE 0 END) AS match_count
|FROM instr_group_test
|GROUP BY substr
|HAVING match_count > 0
|ORDER BY substr
|""".stripMargin)
.collect()
// For the input data, only "test" appears within "str" values, and it occurs 3 times.
assert(result.length == 1)
assert(result(0).getString(0) == "test")
assert(result(0).getLong(1) == 3L)

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}

test("test instr function - in where clause") {
val data =
Seq(("hello world", "world"), ("hello", "world"), ("testing", "test"), ("abc", "def"))

val df = spark.createDataFrame(data).toDF("str", "substr")
val result = df
.filter("instr(str, substr) = 1")
.select("str")
.collect()
.map(_.getString(0))

assert(result.length >= 1)
}
}
2 changes: 2 additions & 0 deletions native-engine/datafusion-ext-functions/src/lib.rs
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@ mod spark_dates;
pub mod spark_get_json_object;
mod spark_hash;
mod spark_initcap;
mod spark_instr;
mod spark_isnan;
mod spark_make_array;
mod spark_make_decimal;
Expand Down Expand Up @@ -91,6 +92,7 @@ pub fn create_auron_ext_function(
Arc::new(spark_normalize_nan_and_zero::spark_normalize_nan_and_zero)
}
"Spark_IsNaN" => Arc::new(spark_isnan::spark_isnan),
"Spark_Instr" => Arc::new(spark_instr::spark_instr),
_ => df_unimplemented_err!("spark ext function not implemented: {name}")?,
})
}
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