feat: approx_quantile dataframe function

Adds the approx_quantile() dataframe function, and exports it in the
prelude.

Author: domodwyer

datafusion/src/logical_plan/expr.rs

@@ -1635,6 +1635,15 @@ pub fn approx_distinct(expr: Expr) -> Expr {
     }
 }
 
+/// Calculate an approximation of the specified `quantile` for `expr`.
+pub fn approx_quantile(expr: Expr, quantile: Expr) -> Expr {
+    Expr::AggregateFunction {
+        fun: aggregates::AggregateFunction::ApproxQuantile,
+        distinct: false,
+        args: vec![expr, quantile],
+    }
+}
+
 // TODO(kszucs): this seems buggy, unary_scalar_expr! is used for many
 // varying arity functions
 /// Create an convenience function representing a unary scalar function

datafusion/src/logical_plan/mod.rs

@@ -36,13 +36,13 @@ pub use builder::{
 pub use dfschema::{DFField, DFSchema, DFSchemaRef, ToDFSchema};
 pub use display::display_schema;
 pub use expr::{
-    abs, acos, and, approx_distinct, array, ascii, asin, atan, avg, binary_expr,
-    bit_length, btrim, case, ceil, character_length, chr, col, columnize_expr,
-    combine_filters, concat, concat_ws, cos, count, count_distinct, create_udaf,
-    create_udf, date_part, date_trunc, digest, exp, exprlist_to_fields, floor, in_list,
-    initcap, left, length, lit, lit_timestamp_nano, ln, log10, log2, lower, lpad, ltrim,
-    max, md5, min, normalize_col, normalize_cols, now, octet_length, or, random,
-    regexp_match, regexp_replace, repeat, replace, replace_col, reverse,
+    abs, acos, and, approx_distinct, approx_quantile, array, ascii, asin, atan, avg,
+    binary_expr, bit_length, btrim, case, ceil, character_length, chr, col,
+    columnize_expr, combine_filters, concat, concat_ws, cos, count, count_distinct,
+    create_udaf, create_udf, date_part, date_trunc, digest, exp, exprlist_to_fields,
+    floor, in_list, initcap, left, length, lit, lit_timestamp_nano, ln, log10, log2,
+    lower, lpad, ltrim, max, md5, min, normalize_col, normalize_cols, now, octet_length,
+    or, random, regexp_match, regexp_replace, repeat, replace, replace_col, reverse,
     rewrite_sort_cols_by_aggs, right, round, rpad, rtrim, sha224, sha256, sha384, sha512,
     signum, sin, split_part, sqrt, starts_with, strpos, substr, sum, tan, to_hex,
     translate, trim, trunc, unalias, unnormalize_col, unnormalize_cols, upper, when,

datafusion/src/prelude.rs

@@ -30,10 +30,10 @@ pub use crate::execution::context::{ExecutionConfig, ExecutionContext};
 pub use crate::execution::options::AvroReadOptions;
 pub use crate::execution::options::{CsvReadOptions, NdJsonReadOptions};
 pub use crate::logical_plan::{
-    array, ascii, avg, bit_length, btrim, character_length, chr, col, concat, concat_ws,
-    count, create_udf, date_part, date_trunc, digest, in_list, initcap, left, length,
-    lit, lower, lpad, ltrim, max, md5, min, now, octet_length, random, regexp_match,
-    regexp_replace, repeat, replace, reverse, right, rpad, rtrim, sha224, sha256, sha384,
-    sha512, split_part, starts_with, strpos, substr, sum, to_hex, translate, trim, upper,
-    Column, JoinType, Partitioning,
+    approx_quantile, array, ascii, avg, bit_length, btrim, character_length, chr, col,
+    concat, concat_ws, count, create_udf, date_part, date_trunc, digest, in_list,
+    initcap, left, length, lit, lower, lpad, ltrim, max, md5, min, now, octet_length,
+    random, regexp_match, regexp_replace, repeat, replace, reverse, right, rpad, rtrim,
+    sha224, sha256, sha384, sha512, split_part, starts_with, strpos, substr, sum, to_hex,
+    translate, trim, upper, Column, JoinType, Partitioning,
 };

datafusion/tests/dataframe_functions.rs

@@ -153,6 +153,26 @@ async fn test_fn_btrim_with_chars() -> Result<()> {
     Ok(())
 }
 
+#[tokio::test]
+async fn test_fn_approx_quantile() -> Result<()> {
+    let expr = approx_quantile(col("b"), lit(0.5));
+
+    let expected = vec![
+        "+-------------------------------------+",
+        "| APPROXQUANTILE(test.b,Float64(0.5)) |",
+        "+-------------------------------------+",
+        "| 10                                  |",
+        "+-------------------------------------+",
+    ];
+
+    let df = create_test_table()?;
+    let batches = df.aggregate(vec![], vec![expr]).unwrap().collect().await?;
+
+    assert_batches_eq!(expected, &batches);
+
+    Ok(())
+}
+
 #[tokio::test]
 async fn test_fn_character_length() -> Result<()> {
     let expr = character_length(col("a"));