Remove from_slice and use upstream

datafusion-examples/examples/dataframe_in_memory.rs

@@ -21,7 +21,6 @@ use datafusion::arrow::array::{Int32Array, StringArray};
 use datafusion::arrow::datatypes::{DataType, Field, Schema};
 use datafusion::arrow::record_batch::RecordBatch;
 use datafusion::error::Result;
-use datafusion::from_slice::FromSlice;
 use datafusion::prelude::*;
 
 /// This example demonstrates how to use the DataFrame API against in-memory data.
@@ -37,8 +36,8 @@ async fn main() -> Result<()> {
  let batch = RecordBatch::try_new(
  schema,
  vec![
- Arc::new(StringArray::from_slice(["a", "b", "c", "d"])),
- Arc::new(Int32Array::from_slice([1, 10, 10, 100])),
+ Arc::new(StringArray::from(vec!["a", "b", "c", "d"])),
+ Arc::new(Int32Array::from(vec![1, 10, 10, 100])),
  ],
  )?;
 

datafusion-examples/examples/simple_udaf.rs

@@ -20,7 +20,6 @@
 use datafusion::arrow::{
  array::ArrayRef, array::Float32Array, datatypes::DataType, record_batch::RecordBatch,
 };
-use datafusion::from_slice::FromSlice;
 use datafusion::{error::Result, physical_plan::Accumulator};
 use datafusion::{logical_expr::Volatility, prelude::*, scalar::ScalarValue};
 use datafusion_common::cast::as_float64_array;
@@ -37,11 +36,11 @@ fn create_context() -> Result<SessionContext> {
  // define data in two partitions
  let batch1 = RecordBatch::try_new(
  schema.clone(),
- vec![Arc::new(Float32Array::from_slice([2.0, 4.0, 8.0]))],
+ vec![Arc::new(Float32Array::from(vec![2.0, 4.0, 8.0]))],
  )?;
  let batch2 = RecordBatch::try_new(
  schema.clone(),
- vec![Arc::new(Float32Array::from_slice([64.0]))],
+ vec![Arc::new(Float32Array::from(vec![64.0]))],
  )?;
 
  // declare a new context. In spark API, this corresponds to a new spark SQLsession

datafusion-examples/examples/simple_udf.rs

@@ -24,7 +24,6 @@ use datafusion::{
  logical_expr::Volatility,
 };
 
-use datafusion::from_slice::FromSlice;
 use datafusion::prelude::*;
 use datafusion::{error::Result, physical_plan::functions::make_scalar_function};
 use datafusion_common::cast::as_float64_array;
@@ -43,8 +42,8 @@ fn create_context() -> Result<SessionContext> {
  let batch = RecordBatch::try_new(
  schema,
  vec![
- Arc::new(Float32Array::from_slice([2.1, 3.1, 4.1, 5.1])),
- Arc::new(Float64Array::from_slice([1.0, 2.0, 3.0, 4.0])),
+ Arc::new(Float32Array::from(vec![2.1, 3.1, 4.1, 5.1])),
+ Arc::new(Float64Array::from(vec![1.0, 2.0, 3.0, 4.0])),
  ],
  )?;
 

datafusion/common/src/lib.rs

@@ -21,7 +21,6 @@ pub mod config;
 pub mod delta;
 mod dfschema;
 mod error;
-pub mod from_slice;
 mod join_type;
 pub mod parsers;
 #[cfg(feature = "pyarrow")]

datafusion/common/src/scalar.rs

@@ -3851,7 +3851,6 @@ mod tests {
  use rand::Rng;
 
  use crate::cast::{as_string_array, as_uint32_array, as_uint64_array};
- use crate::from_slice::FromSlice;
 
  use super::*;
 
@@ -4827,26 +4826,26 @@ mod tests {
  let expected = Arc::new(StructArray::from(vec![
  (
  field_a.clone(),
- Arc::new(Int32Array::from_slice([23, 23])) as ArrayRef,
+ Arc::new(Int32Array::from(vec![23, 23])) as ArrayRef,
  ),
  (
  field_b.clone(),
- Arc::new(BooleanArray::from_slice([false, false])) as ArrayRef,
+ Arc::new(BooleanArray::from(vec![false, false])) as ArrayRef,
  ),
  (
  field_c.clone(),
- Arc::new(StringArray::from_slice(["Hello", "Hello"])) as ArrayRef,
+ Arc::new(StringArray::from(vec!["Hello", "Hello"])) as ArrayRef,
  ),
  (
  field_d.clone(),
  Arc::new(StructArray::from(vec![
  (
  field_e.clone(),
- Arc::new(Int16Array::from_slice([2, 2])) as ArrayRef,
+ Arc::new(Int16Array::from(vec![2, 2])) as ArrayRef,
  ),
  (
  field_f.clone(),
- Arc::new(Int64Array::from_slice([3, 3])) as ArrayRef,
+ Arc::new(Int64Array::from(vec![3, 3])) as ArrayRef,
  ),
  ])) as ArrayRef,
  ),
@@ -4922,27 +4921,26 @@ mod tests {
  let expected = Arc::new(StructArray::from(vec![
  (
  field_a,
- Arc::new(Int32Array::from_slice([23, 7, -1000])) as ArrayRef,
+ Arc::new(Int32Array::from(vec![23, 7, -1000])) as ArrayRef,
  ),
  (
  field_b,
- Arc::new(BooleanArray::from_slice([false, true, true])) as ArrayRef,
+ Arc::new(BooleanArray::from(vec![false, true, true])) as ArrayRef,
  ),
  (
  field_c,
- Arc::new(StringArray::from_slice(["Hello", "World", "!!!!!"]))
- as ArrayRef,
+ Arc::new(StringArray::from(vec!["Hello", "World", "!!!!!"])) as ArrayRef,
  ),
  (
  field_d,
  Arc::new(StructArray::from(vec![
  (
  field_e,
- Arc::new(Int16Array::from_slice([2, 4, 6])) as ArrayRef,
+ Arc::new(Int16Array::from(vec![2, 4, 6])) as ArrayRef,
  ),
  (
  field_f,
- Arc::new(Int64Array::from_slice([3, 5, 7])) as ArrayRef,
+ Arc::new(Int64Array::from(vec![3, 5, 7])) as ArrayRef,
  ),
  ])) as ArrayRef,
  ),
@@ -5003,8 +5001,7 @@ mod tests {
  let expected = StructArray::from(vec![
  (
  field_a.clone(),
- Arc::new(StringArray::from_slice(["First", "Second", "Third"]))
- as ArrayRef,
+ Arc::new(StringArray::from(vec!["First", "Second", "Third"])) as ArrayRef,
  ),
  (
  field_primitive_list.clone(),

datafusion/common/src/utils.rs

@@ -388,24 +388,22 @@ pub mod datafusion_strsim {
 
 #[cfg(test)]
 mod tests {
+ use crate::ScalarValue;
+ use crate::ScalarValue::Null;
  use arrow::array::Float64Array;
  use arrow_array::Array;
  use std::ops::Range;
  use std::sync::Arc;
 
- use crate::from_slice::FromSlice;
- use crate::ScalarValue;
- use crate::ScalarValue::Null;
-
  use super::*;
 
  #[test]
  fn test_bisect_linear_left_and_right() -> Result<()> {
  let arrays: Vec<ArrayRef> = vec![
- Arc::new(Float64Array::from_slice([5.0, 7.0, 8.0, 9., 10.])),
- Arc::new(Float64Array::from_slice([2.0, 3.0, 3.0, 4.0, 5.0])),
- Arc::new(Float64Array::from_slice([5.0, 7.0, 8.0, 10., 11.0])),
- Arc::new(Float64Array::from_slice([15.0, 13.0, 8.0, 5., 0.0])),
+ Arc::new(Float64Array::from(vec![5.0, 7.0, 8.0, 9., 10.])),
+ Arc::new(Float64Array::from(vec![2.0, 3.0, 3.0, 4.0, 5.0])),
+ Arc::new(Float64Array::from(vec![5.0, 7.0, 8.0, 10., 11.0])),
+ Arc::new(Float64Array::from(vec![15.0, 13.0, 8.0, 5., 0.0])),
  ];
  let search_tuple: Vec<ScalarValue> = vec![
  ScalarValue::Float64(Some(8.0)),
@@ -478,9 +476,8 @@ mod tests {
  #[test]
  fn test_bisect_linear_left_and_right_diff_sort() -> Result<()> {
  // Descending, left
- let arrays: Vec<ArrayRef> = vec![Arc::new(Float64Array::from_slice([
- 4.0, 3.0, 2.0, 1.0, 0.0,
- ]))];
+ let arrays: Vec<ArrayRef> =
+ vec![Arc::new(Float64Array::from(vec![4.0, 3.0, 2.0, 1.0, 0.0]))];
  let search_tuple: Vec<ScalarValue> = vec![ScalarValue::Float64(Some(4.0))];
  let ords = [SortOptions {
  descending: true,
@@ -492,9 +489,8 @@ mod tests {
  assert_eq!(res, 0);
 
  // Descending, right
- let arrays: Vec<ArrayRef> = vec![Arc::new(Float64Array::from_slice([
- 4.0, 3.0, 2.0, 1.0, 0.0,
- ]))];
+ let arrays: Vec<ArrayRef> =
+ vec![Arc::new(Float64Array::from(vec![4.0, 3.0, 2.0, 1.0, 0.0]))];
  let search_tuple: Vec<ScalarValue> = vec![ScalarValue::Float64(Some(4.0))];
  let ords = [SortOptions {
  descending: true,
@@ -507,7 +503,7 @@ mod tests {
 
  // Ascending, left
  let arrays: Vec<ArrayRef> =
- vec![Arc::new(Float64Array::from_slice([5.0, 7.0, 8.0, 9., 10.]))];
+ vec![Arc::new(Float64Array::from(vec![5.0, 7.0, 8.0, 9., 10.]))];
  let search_tuple: Vec<ScalarValue> = vec![ScalarValue::Float64(Some(7.0))];
  let ords = [SortOptions {
  descending: false,
@@ -520,7 +516,7 @@ mod tests {
 
  // Ascending, right
  let arrays: Vec<ArrayRef> =
- vec![Arc::new(Float64Array::from_slice([5.0, 7.0, 8.0, 9., 10.]))];
+ vec![Arc::new(Float64Array::from(vec![5.0, 7.0, 8.0, 9., 10.]))];
  let search_tuple: Vec<ScalarValue> = vec![ScalarValue::Float64(Some(7.0))];
  let ords = [SortOptions {
  descending: false,
@@ -532,8 +528,8 @@ mod tests {
  assert_eq!(res, 2);
 
  let arrays: Vec<ArrayRef> = vec![
- Arc::new(Float64Array::from_slice([5.0, 7.0, 8.0, 8.0, 9., 10.])),
- Arc::new(Float64Array::from_slice([10.0, 9.0, 8.0, 7.5, 7., 6.])),
+ Arc::new(Float64Array::from(vec![5.0, 7.0, 8.0, 8.0, 9., 10.])),
+ Arc::new(Float64Array::from(vec![10.0, 9.0, 8.0, 7.5, 7., 6.])),
  ];
  let search_tuple: Vec<ScalarValue> = vec![
  ScalarValue::Float64(Some(8.0)),
@@ -564,8 +560,8 @@ mod tests {
  #[test]
  fn test_evaluate_partition_ranges() -> Result<()> {
  let arrays: Vec<ArrayRef> = vec![
- Arc::new(Float64Array::from_slice([1.0, 1.0, 1.0, 2.0, 2.0, 2.0])),
- Arc::new(Float64Array::from_slice([4.0, 4.0, 3.0, 2.0, 1.0, 1.0])),
+ Arc::new(Float64Array::from(vec![1.0, 1.0, 1.0, 2.0, 2.0, 2.0])),
+ Arc::new(Float64Array::from(vec![4.0, 4.0, 3.0, 2.0, 1.0, 1.0])),
  ];
  let n_row = arrays[0].len();
  let options: Vec<SortOptions> = vec![
@@ -641,10 +637,10 @@ mod tests {
  #[test]
  fn test_get_arrayref_at_indices() -> Result<()> {
  let arrays: Vec<ArrayRef> = vec![
- Arc::new(Float64Array::from_slice([5.0, 7.0, 8.0, 9., 10.])),
- Arc::new(Float64Array::from_slice([2.0, 3.0, 3.0, 4.0, 5.0])),
- Arc::new(Float64Array::from_slice([5.0, 7.0, 8.0, 10., 11.0])),
- Arc::new(Float64Array::from_slice([15.0, 13.0, 8.0, 5., 0.0])),
+ Arc::new(Float64Array::from(vec![5.0, 7.0, 8.0, 9., 10.])),
+ Arc::new(Float64Array::from(vec![2.0, 3.0, 3.0, 4.0, 5.0])),
+ Arc::new(Float64Array::from(vec![5.0, 7.0, 8.0, 10., 11.0])),
+ Arc::new(Float64Array::from(vec![15.0, 13.0, 8.0, 5., 0.0])),
  ];
 
  let row_indices_vec: Vec<Vec<u32>> = vec![

datafusion/core/benches/data_utils/mod.rs

@@ -27,7 +27,6 @@ use arrow::{
 };
 use datafusion::datasource::MemTable;
 use datafusion::error::Result;
-use datafusion::from_slice::FromSlice;
 use rand::rngs::StdRng;
 use rand::seq::SliceRandom;
 use rand::{Rng, SeedableRng};
@@ -131,7 +130,7 @@ fn create_record_batch(
  schema,
  vec![
  Arc::new(StringArray::from(keys)),
- Arc::new(Float32Array::from_slice(vec![i as f32; batch_size])),
+ Arc::new(Float32Array::from(vec![i as f32; batch_size])),
  Arc::new(Float64Array::from(values)),
  Arc::new(UInt64Array::from(integer_values_wide)),
  Arc::new(UInt64Array::from(integer_values_narrow)),