swiftide_integrations/parquet/
loader.rs1use anyhow::{Context as _, Result};
2use fs_err::tokio::File;
3use futures_util::StreamExt as _;
4use parquet::arrow::{ParquetRecordBatchStreamBuilder, ProjectionMask};
5use parquet_arrow_array::{LargeStringArray, StringArray, StringViewArray};
6use swiftide_core::{
7 Loader,
8 indexing::{IndexingStream, TextNode},
9};
10use tokio::runtime::Handle;
11
12use super::Parquet;
13
14impl Loader for Parquet {
15 type Output = String;
16
17 fn into_stream(self) -> IndexingStream<String> {
18 let mut builder = tokio::task::block_in_place(|| {
19 Handle::current().block_on(async {
20 let file = File::open(self.path).await.expect("Failed to open file");
21
22 ParquetRecordBatchStreamBuilder::new(file)
23 .await
24 .context("Failed to load builder")
25 .unwrap()
26 .with_batch_size(self.batch_size)
27 })
28 });
29
30 let file_metadata = builder.metadata().file_metadata().clone();
31 dbg!(file_metadata.schema_descr().columns());
32 let column_idx = file_metadata
33 .schema()
34 .get_fields()
35 .iter()
36 .enumerate()
37 .find_map(|(pos, column)| {
38 if self.column_name == column.name() {
39 Some(pos)
40 } else {
41 None
42 }
43 })
44 .unwrap_or_else(|| panic!("Column {} not found in dataset", self.column_name));
45
46 let mask = ProjectionMask::roots(file_metadata.schema_descr(), [column_idx]);
47 builder = builder.with_projection(mask);
48
49 let stream = builder.build().expect("Failed to build parquet builder");
50
51 let swiftide_stream = stream.flat_map_unordered(None, move |result_batch| {
52 let Ok(batch) = result_batch else {
53 let new_result: Result<TextNode> = Err(anyhow::anyhow!(result_batch.unwrap_err()));
54
55 return vec![new_result].into();
56 };
57 assert!(batch.num_columns() == 1, "Number of columns _must_ be 1");
58
59 let column = batch.column(0); let node_values = if let Some(values) = column.as_any().downcast_ref::<StringArray>() {
61 values
62 .iter()
63 .flatten()
64 .map(TextNode::from)
65 .map(Ok)
66 .collect::<Vec<_>>()
67 } else if let Some(values) = column.as_any().downcast_ref::<LargeStringArray>() {
68 values
69 .iter()
70 .flatten()
71 .map(TextNode::from)
72 .map(Ok)
73 .collect::<Vec<_>>()
74 } else if let Some(values) = column.as_any().downcast_ref::<StringViewArray>() {
75 values
76 .iter()
77 .flatten()
78 .map(TextNode::from)
79 .map(Ok)
80 .collect::<Vec<_>>()
81 } else {
82 let new_result: Result<TextNode> = Err(anyhow::anyhow!(
83 "Parquet column is not a string array (got {:?})",
84 column.data_type()
85 ));
86
87 return vec![new_result].into();
88 };
89
90 IndexingStream::iter(node_values)
91 });
92
93 swiftide_stream.boxed().into()
94
95 }
97
98 fn into_stream_boxed(self: Box<Self>) -> IndexingStream<String> {
99 self.into_stream()
100 }
101}
102
103#[cfg(test)]
104mod tests {
105 use std::path::PathBuf;
106
107 use futures_util::TryStreamExt as _;
108
109 use super::*;
110
111 #[test_log::test(tokio::test(flavor = "multi_thread"))]
112 async fn test_parquet_loader() {
113 let mut path = PathBuf::from(env!("CARGO_MANIFEST_DIR"));
114 path.push("src/parquet/test.parquet");
115 dbg!(&path);
116
117 let loader = Parquet::builder()
118 .path(path)
119 .column_name("chunk")
120 .build()
121 .unwrap();
122
123 let result = loader.into_stream().try_collect::<Vec<_>>().await.unwrap();
124
125 let expected = [TextNode::new("hello"), TextNode::new("world")];
126 assert_eq!(result, expected);
127 }
128}