alamb commented on code in PR #12847:
URL: https://github.com/apache/datafusion/pull/12847#discussion_r1801799363
##########
datafusion/core/tests/fuzz_cases/aggregation_fuzzer/fuzzer.rs:
##########
@@ -305,3 +327,172 @@ impl AggregationFuzzTestTask {
)
}
}
+
+/// Pretty prints the `RecordBatch`es, limited to the first 100 rows
+fn format_batches_with_limit(batches: &[RecordBatch]) -> impl
std::fmt::Display {
Review Comment:
without limiting the size of the output, the output is overwhelming
##########
datafusion/core/tests/fuzz_cases/aggregate_fuzz.rs:
##########
@@ -45,299 +45,149 @@ use rand::{Rng, SeedableRng};
use tokio::task::JoinSet;
use crate::fuzz_cases::aggregation_fuzzer::{
- AggregationFuzzerBuilder, ColumnDescr, DatasetGeneratorConfig,
+ AggregationFuzzerBuilder, ColumnDescr, DatasetGeneratorConfig,
QueryBuilder,
};
// ========================================================================
// The new aggregation fuzz tests based on [`AggregationFuzzer`]
// ========================================================================
+//
+// Notes on tests:
+//
+// Since the supported types differ for each aggregation function, the tests
+// below are structured so they enumerate each different aggregate function.
+//
+// The test framework handles varying combinations of arguments (data types),
+// sortedness, and grouping parameters
+//
+// TODO: Test on floating point values (where output needs to be compared with
some
Review Comment:
I plan to work on these tests next. First I will add coverage for StringView
/ BinaryView
##########
datafusion/core/tests/fuzz_cases/aggregate_fuzz.rs:
##########
@@ -45,299 +45,149 @@ use rand::{Rng, SeedableRng};
use tokio::task::JoinSet;
use crate::fuzz_cases::aggregation_fuzzer::{
- AggregationFuzzerBuilder, ColumnDescr, DatasetGeneratorConfig,
+ AggregationFuzzerBuilder, ColumnDescr, DatasetGeneratorConfig,
QueryBuilder,
};
// ========================================================================
// The new aggregation fuzz tests based on [`AggregationFuzzer`]
// ========================================================================
+//
+// Notes on tests:
+//
+// Since the supported types differ for each aggregation function, the tests
+// below are structured so they enumerate each different aggregate function.
+//
+// The test framework handles varying combinations of arguments (data types),
+// sortedness, and grouping parameters
+//
+// TODO: Test on floating point values (where output needs to be compared with
some
+// acceptable range due to floating point rounding)
+//
+// TODO: test other aggregate functions
+// - AVG (unstable given the wide range of inputs)
+//
+// TODO: specific test for ordering (ensure all group by columns are ordered)
-// TODO: write more test case to cover more `group by`s and `aggregation
function`s
-// TODO: maybe we can use macro to simply the case creating
-
-/// Fuzz test for `basic prim aggr(sum/sum distinct/max/min/count/avg)` + `no
group by`
-#[tokio::test(flavor = "multi_thread")]
-async fn test_basic_prim_aggr_no_group() {
- let builder = AggregationFuzzerBuilder::default();
-
- // Define data generator config
- let columns = vec![ColumnDescr::new("a", DataType::Int32)];
-
- let data_gen_config = DatasetGeneratorConfig {
- columns,
- rows_num_range: (512, 1024),
- sort_keys_set: Vec::new(),
- };
-
- // Build fuzzer
- let fuzzer = builder
- .data_gen_config(data_gen_config)
- .data_gen_rounds(16)
- .add_sql("SELECT sum(a) FROM fuzz_table")
- .add_sql("SELECT sum(distinct a) FROM fuzz_table")
- .add_sql("SELECT max(a) FROM fuzz_table")
- .add_sql("SELECT min(a) FROM fuzz_table")
- .add_sql("SELECT count(a) FROM fuzz_table")
- .add_sql("SELECT count(distinct a) FROM fuzz_table")
- .add_sql("SELECT avg(a) FROM fuzz_table")
- .table_name("fuzz_table")
- .build();
-
- fuzzer.run().await
-}
-
-/// Fuzz test for `basic prim aggr(sum/sum distinct/max/min/count/avg)` +
`group by single int64`
-#[tokio::test(flavor = "multi_thread")]
-async fn test_basic_prim_aggr_group_by_single_int64() {
- let builder = AggregationFuzzerBuilder::default();
-
- // Define data generator config
- let columns = vec![
- ColumnDescr::new("a", DataType::Int32),
- ColumnDescr::new("b", DataType::Int64),
- ColumnDescr::new("c", DataType::Int64),
- ];
- let sort_keys_set = vec![
- vec!["b".to_string()],
- vec!["c".to_string(), "b".to_string()],
- ];
- let data_gen_config = DatasetGeneratorConfig {
- columns,
- rows_num_range: (512, 1024),
- sort_keys_set,
- };
-
- // Build fuzzer
- let fuzzer = builder
- .data_gen_config(data_gen_config)
- .data_gen_rounds(16)
- .add_sql("SELECT b, sum(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, sum(distinct a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, max(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, min(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, count(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, count(distinct a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, avg(a) FROM fuzz_table GROUP BY b")
- .table_name("fuzz_table")
- .build();
-
- fuzzer.run().await;
-}
-
-/// Fuzz test for `basic prim aggr(sum/sum distinct/max/min/count/avg)` +
`group by single string`
#[tokio::test(flavor = "multi_thread")]
-async fn test_basic_prim_aggr_group_by_single_string() {
- let builder = AggregationFuzzerBuilder::default();
-
- // Define data generator config
- let columns = vec![
- ColumnDescr::new("a", DataType::Int32),
- ColumnDescr::new("b", DataType::Utf8),
- ColumnDescr::new("c", DataType::Int64),
- ];
- let sort_keys_set = vec![
- vec!["b".to_string()],
- vec!["c".to_string(), "b".to_string()],
- ];
- let data_gen_config = DatasetGeneratorConfig {
- columns,
- rows_num_range: (512, 1024),
- sort_keys_set,
- };
-
- // Build fuzzer
- let fuzzer = builder
- .data_gen_config(data_gen_config)
- .data_gen_rounds(16)
- .add_sql("SELECT b, sum(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, sum(distinct a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, max(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, min(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, count(a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, count(distinct a) FROM fuzz_table GROUP BY b")
- .add_sql("SELECT b, avg(a) FROM fuzz_table GROUP BY b")
- .table_name("fuzz_table")
- .build();
-
- fuzzer.run().await;
+async fn test_min() {
+ let data_gen_config = baseline_config();
+
+ // Queries like SELECT min(a) FROM fuzz_table GROUP BY b
+ let query_builder = QueryBuilder::new()
Review Comment:
The major "innovation" of this PR is to automatically generate the queries
as well to increase coverage (e.g. different numbers of group columns, etc)
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