16565982454

Committed 28 Jul 2025 09:57AM UTC coverage: 81.767% (-0.02%) from 81.789%

Build # 16565982454

Build Type

Pull #4031

github

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web-flow

Commit Message

Merge 73cac1802 into a0efcbe7a

Pull Request Pull Request #4031: zip compute function

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/vortex-datafusion/src/persistent/format.rs

// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright the Vortex contributors

use std::any::Any;
use std::fmt::{Debug, Formatter};
use std::sync::Arc;

use async_trait::async_trait;
use datafusion::arrow::datatypes::{Schema, SchemaRef};
use datafusion::catalog::Session;
use datafusion::common::parsers::CompressionTypeVariant;
use datafusion::common::runtime::SpawnedTask;
use datafusion::common::stats::Precision;
use datafusion::common::{
    ColumnStatistics, DataFusionError, GetExt, Result as DFResult, Statistics,
    config_datafusion_err, not_impl_err,
};
use datafusion::datasource::file_format::file_compression_type::FileCompressionType;
use datafusion::datasource::file_format::{FileFormat, FileFormatFactory};
use datafusion::datasource::physical_plan::{
    FileScanConfig, FileScanConfigBuilder, FileSinkConfig, FileSource,
};
use datafusion::datasource::sink::DataSinkExec;
use datafusion::datasource::source::DataSourceExec;
use datafusion::logical_expr::dml::InsertOp;
use datafusion::physical_expr::LexRequirement;
use datafusion::physical_plan::ExecutionPlan;
use futures::{FutureExt, StreamExt as _, TryStreamExt as _, stream};
use itertools::Itertools;
use object_store::{ObjectMeta, ObjectStore};
use vortex::dtype::DType;
use vortex::dtype::arrow::FromArrowType;
use vortex::error::{VortexExpect, VortexResult, vortex_err};
use vortex::file::VORTEX_FILE_EXTENSION;
use vortex::metrics::VortexMetrics;
use vortex::session::VortexSession;
use vortex::stats;
use vortex::stats::{Stat, StatsProviderExt, StatsSet};

use super::cache::VortexFileCache;
use super::sink::VortexSink;
use super::source::VortexSource;
use crate::PrecisionExt as _;
use crate::convert::TryToDataFusion;

/// Vortex implementation of a DataFusion [`FileFormat`].
pub struct VortexFormat {
    session: Arc<VortexSession>,
    file_cache: VortexFileCache,
    opts: VortexFormatOptions,
}

impl Debug for VortexFormat {
    fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
        f.debug_struct("VortexFormat")
            .field("opts", &self.opts)
            .finish()
    }
}

/// Options to configure the [`VortexFormat`].
#[derive(Debug)]
pub struct VortexFormatOptions {
    /// The size of the in-memory [`vortex::file::Footer`] cache.
    pub footer_cache_size_mb: usize,
    /// The size of the in-memory segment cache.
    pub segment_cache_size_mb: usize,
}

impl Default for VortexFormatOptions {
    fn default() -> Self {
        Self {
            footer_cache_size_mb: 64,
            segment_cache_size_mb: 0,
        }
    }
}

/// Minimal factory to create [`VortexFormat`] instances.
#[derive(Default, Debug)]
pub struct VortexFormatFactory {
    session: Arc<VortexSession>,
}

impl GetExt for VortexFormatFactory {
    fn get_ext(&self) -> String {
        VORTEX_FILE_EXTENSION.to_string()
    }
}

impl FileFormatFactory for VortexFormatFactory {
    #[allow(clippy::disallowed_types)]
    fn create(
        &self,
        _state: &dyn Session,
        format_options: &std::collections::HashMap<String, String>,
    ) -> DFResult<Arc<dyn FileFormat>> {
        if !format_options.is_empty() {
            return Err(config_datafusion_err!(
                "Vortex tables don't support any options"
            ));
        }

        Ok(Arc::new(VortexFormat::new(self.session.clone())))
    }

    fn default(&self) -> Arc<dyn FileFormat> {
        Arc::new(VortexFormat::default())
    }

    fn as_any(&self) -> &dyn Any {
        self
    }
}

impl Default for VortexFormat {
    fn default() -> Self {
        Self::new(Arc::new(VortexSession::default()))
    }
}

impl VortexFormat {
    /// Create a new instance of the [`VortexFormat`].
    pub fn new(session: Arc<VortexSession>) -> Self {
        let opts = VortexFormatOptions::default();
        Self {
            session: session.clone(),
            file_cache: VortexFileCache::new(
                opts.footer_cache_size_mb,
                opts.segment_cache_size_mb,
                session,
            ),
            opts,
        }
    }

    /// Return the format specific configuration
    pub fn options(&self) -> &VortexFormatOptions {
        &self.opts
    }
}

#[async_trait]
impl FileFormat for VortexFormat {
    fn as_any(&self) -> &dyn Any {
        self
    }

    fn compression_type(&self) -> Option<FileCompressionType> {
        None
    }

    fn get_ext(&self) -> String {
        VORTEX_FILE_EXTENSION.to_string()
    }

    fn get_ext_with_compression(
        &self,
        file_compression_type: &FileCompressionType,
    ) -> DFResult<String> {
        match file_compression_type.get_variant() {
            CompressionTypeVariant::UNCOMPRESSED => Ok(self.get_ext()),
            _ => Err(DataFusionError::Internal(
                "Vortex does not support file level compression.".into(),
            )),
        }
    }

    async fn infer_schema(
        &self,
        state: &dyn Session,
        store: &Arc<dyn ObjectStore>,
        objects: &[ObjectMeta],
    ) -> DFResult<SchemaRef> {
        let mut file_schemas = stream::iter(objects.iter().cloned())
            .map(|o| {
                let store = store.clone();
                let cache = self.file_cache.clone();
                SpawnedTask::spawn(async move {
                    let vxf = cache.try_get(&o, store).await?;
                    let inferred_schema = vxf.dtype().to_arrow_schema()?;
                    VortexResult::Ok((o.location, inferred_schema))
                })
                .map(|f| f.vortex_expect("Failed to spawn infer_schema"))
            })
            .buffer_unordered(state.config_options().execution.meta_fetch_concurrency)
            .try_collect::<Vec<_>>()
            .await
            .map_err(|e| DataFusionError::Execution(format!("Failed to infer schema: {e}")))?;

        // Get consistent order of schemas for `Schema::try_merge`, as some filesystems don't have deterministic listing orders
        file_schemas.sort_by(|(l1, _), (l2, _)| l1.cmp(l2));
        let file_schemas = file_schemas.into_iter().map(|(_, schema)| schema);

        Ok(Arc::new(Schema::try_merge(file_schemas)?))
    }

    #[cfg_attr(feature = "tracing", tracing::instrument(skip_all, fields(location = object.location.as_ref()
    )))]
    async fn infer_stats(
        &self,
        _state: &dyn Session,
        store: &Arc<dyn ObjectStore>,
        table_schema: SchemaRef,
        object: &ObjectMeta,
    ) -> DFResult<Statistics> {
        let object = object.clone();
        let store = store.clone();
        let cache = self.file_cache.clone();
        SpawnedTask::spawn(async move {
            let vxf = cache.try_get(&object, store.clone()).await.map_err(|e| {
                DataFusionError::Execution(format!(
                    "Failed to open Vortex file {}: {e}",
                    object.location
                ))
            })?;

            let struct_dtype = vxf
                .dtype()
                .as_struct()
                .vortex_expect("dtype is not a struct");

            // Evaluate the statistics for each column that we are able to return to DataFusion.
            let Some(file_stats) = vxf.file_stats() else {
                // If the file has no column stats, the best we can do is return a row count.
                return Ok(Statistics {
                    num_rows: Precision::Exact(
                        usize::try_from(vxf.row_count())
                            .map_err(|_| vortex_err!("Row count overflow"))
                            .vortex_expect("Row count overflow"),
                    ),
                    total_byte_size: Precision::Absent,
                    column_statistics: vec![ColumnStatistics::default(); struct_dtype.nfields()],
                });
            };

            let stats = table_schema
                .fields()
                .iter()
                .map(|field| struct_dtype.find(field.name()))
                .map(|idx| match idx {
                    None => StatsSet::default(),
                    Some(id) => file_stats[id].clone(),
                })
                .collect_vec();

            let total_byte_size = stats
                .iter()
                .map(|stats_set| {
                    stats_set
                        .get_as::<usize>(Stat::UncompressedSizeInBytes)
                        .unwrap_or_else(|| stats::Precision::inexact(0_usize))
                })
                .fold(stats::Precision::exact(0_usize), |acc, stats_set| {
                    acc.zip(stats_set).map(|(acc, stats_set)| acc + stats_set)
                });

            // Sum up the total byte size across all the columns.
            let total_byte_size = total_byte_size.to_df();

            let column_statistics = stats
                .into_iter()
                .zip(table_schema.fields().iter())
                .map(|(stats_set, field)| {
                    let null_count = stats_set.get_as::<usize>(Stat::NullCount);
                    let min = stats_set
                        .get_scalar(Stat::Min, &DType::from_arrow(field.as_ref()))
                        .and_then(|n| n.map(|n| n.try_to_df().ok()).transpose());

                    let max = stats_set
                        .get_scalar(Stat::Max, &DType::from_arrow(field.as_ref()))
                        .and_then(|n| n.map(|n| n.try_to_df().ok()).transpose());

                    ColumnStatistics {
                        null_count: null_count.to_df(),
                        max_value: max.to_df(),
                        min_value: min.to_df(),
                        sum_value: Precision::Absent,
                        distinct_count: stats_set
                            .get_as::<bool>(Stat::IsConstant)
                            .and_then(|is_constant| {
                                is_constant.as_exact().map(|_| Precision::Exact(1))
                            })
                            .unwrap_or(Precision::Absent),
                    }
                })
                .collect::<Vec<_>>();

            Ok(Statistics {
                num_rows: Precision::Exact(
                    usize::try_from(vxf.row_count())
                        .map_err(|_| vortex_err!("Row count overflow"))
                        .vortex_expect("Row count overflow"),
                ),
                total_byte_size,
                column_statistics,
            })
        })
        .await
        .vortex_expect("Failed to spawn infer_stats")
    }

    async fn create_physical_plan(
        &self,
        _state: &dyn Session,
        file_scan_config: FileScanConfig,
    ) -> DFResult<Arc<dyn ExecutionPlan>> {
        if file_scan_config
            .file_groups
            .iter()
            .flat_map(|fg| fg.files())
            .any(|f| f.range.is_some())
        {
            return not_impl_err!("File level partitioning isn't implemented yet for Vortex");
        }

        if !file_scan_config.table_partition_cols.is_empty() {
            return not_impl_err!("Hive style partitioning isn't implemented yet for Vortex");
        }

        if !file_scan_config.output_ordering.is_empty() {
            return not_impl_err!("Vortex doesn't support output ordering");
        }

        let source = VortexSource::new(self.file_cache.clone(), self.session.metrics().clone());
        Ok(DataSourceExec::from_data_source(
            FileScanConfigBuilder::from(file_scan_config)
                .with_source(Arc::new(source))
                .build(),
        ))
    }

    async fn create_writer_physical_plan(
        &self,
        input: Arc<dyn ExecutionPlan>,
        _state: &dyn Session,
        conf: FileSinkConfig,
        order_requirements: Option<LexRequirement>,
    ) -> DFResult<Arc<dyn ExecutionPlan>> {
        if conf.insert_op != InsertOp::Append {
            return not_impl_err!("Overwrites are not implemented yet for Vortex");
        }

        if !conf.table_partition_cols.is_empty() {
            return not_impl_err!("Hive style partitioning isn't implemented yet for Vortex");
        }

        let schema = conf.output_schema().clone();
        let sink = Arc::new(VortexSink::new(conf, schema));

        Ok(Arc::new(DataSinkExec::new(input, sink, order_requirements)) as _)
    }

    fn file_source(&self) -> Arc<dyn FileSource> {
        Arc::new(VortexSource::new(
            self.file_cache.clone(),
            VortexMetrics::default(),
        ))
    }
}

#[cfg(test)]
mod tests {
    use datafusion::execution::SessionStateBuilder;
    use datafusion::prelude::SessionContext;
    use tempfile::TempDir;

    use super::*;
    use crate::persistent::register_vortex_format_factory;

    #[tokio::test]
    async fn create_table() {
        let dir = TempDir::new().unwrap();

        let factory: VortexFormatFactory = Default::default();
        let mut session_state_builder = SessionStateBuilder::new().with_default_features();
        register_vortex_format_factory(factory, &mut session_state_builder);
        let session = SessionContext::new_with_state(session_state_builder.build());

        let df = session
            .sql(&format!(
                "CREATE EXTERNAL TABLE my_tbl \
                (c1 VARCHAR NOT NULL, c2 INT NOT NULL) \
                STORED AS vortex LOCATION '{}'",
                dir.path().to_str().unwrap()
            ))
            .await
            .unwrap();

        assert_eq!(df.count().await.unwrap(), 0);
    }

    #[tokio::test]
    #[should_panic]
    async fn fail_table_config() {
        let dir = TempDir::new().unwrap();

        let factory: VortexFormatFactory = Default::default();
        let mut session_state_builder = SessionStateBuilder::new().with_default_features();
        register_vortex_format_factory(factory, &mut session_state_builder);
        let session = SessionContext::new_with_state(session_state_builder.build());

        session
            .sql(&format!(
                "CREATE EXTERNAL TABLE my_tbl \
                (c1 VARCHAR NOT NULL, c2 INT NOT NULL) \
                STORED AS vortex LOCATION '{}' \
                OPTIONS( some_key 'value' );",
                dir.path().to_str().unwrap()
            ))
            .await
            .unwrap()
            .collect()
            .await
            .unwrap();
    }
}

1	// SPDX-License-Identifier: Apache-2.0
2	// SPDX-FileCopyrightText: Copyright the Vortex contributors
3
4	use std::any::Any;
5	use std::fmt::{Debug, Formatter};
6	use std::sync::Arc;
7
8	use async_trait::async_trait;
9	use datafusion::arrow::datatypes::{Schema, SchemaRef};
10	use datafusion::catalog::Session;
11	use datafusion::common::parsers::CompressionTypeVariant;
12	use datafusion::common::runtime::SpawnedTask;
13	use datafusion::common::stats::Precision;
14	use datafusion::common::{
15	ColumnStatistics, DataFusionError, GetExt, Result as DFResult, Statistics,
16	config_datafusion_err, not_impl_err,
17	};
18	use datafusion::datasource::file_format::file_compression_type::FileCompressionType;
19	use datafusion::datasource::file_format::{FileFormat, FileFormatFactory};
20	use datafusion::datasource::physical_plan::{
21	FileScanConfig, FileScanConfigBuilder, FileSinkConfig, FileSource,
22	};
23	use datafusion::datasource::sink::DataSinkExec;
24	use datafusion::datasource::source::DataSourceExec;
25	use datafusion::logical_expr::dml::InsertOp;
26	use datafusion::physical_expr::LexRequirement;
27	use datafusion::physical_plan::ExecutionPlan;
28	use futures::{FutureExt, StreamExt as _, TryStreamExt as _, stream};
29	use itertools::Itertools;
30	use object_store::{ObjectMeta, ObjectStore};
31	use vortex::dtype::DType;
32	use vortex::dtype::arrow::FromArrowType;
33	use vortex::error::{VortexExpect, VortexResult, vortex_err};
34	use vortex::file::VORTEX_FILE_EXTENSION;
35	use vortex::metrics::VortexMetrics;
36	use vortex::session::VortexSession;
37	use vortex::stats;
38	use vortex::stats::{Stat, StatsProviderExt, StatsSet};
39
40	use super::cache::VortexFileCache;
41	use super::sink::VortexSink;
42	use super::source::VortexSource;
43	use crate::PrecisionExt as _;
44	use crate::convert::TryToDataFusion;
45
46	/// Vortex implementation of a DataFusion [`FileFormat`].
47	pub struct VortexFormat {
48	session: Arc<VortexSession>,
49	file_cache: VortexFileCache,
50	opts: VortexFormatOptions,
51	}
52
53	impl Debug for VortexFormat {
54	fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {	×
55	f.debug_struct("VortexFormat")	×
56	.field("opts", &self.opts)	×
57	.finish()	×
58	}	×
59	}
60
61	/// Options to configure the [`VortexFormat`].
62	#[derive(Debug)]
63	pub struct VortexFormatOptions {
64	/// The size of the in-memory [`vortex::file::Footer`] cache.
65	pub footer_cache_size_mb: usize,
66	/// The size of the in-memory segment cache.
67	pub segment_cache_size_mb: usize,
68	}
69
70	impl Default for VortexFormatOptions {
71	fn default() -> Self {	20✔
72	Self {	20✔
73	footer_cache_size_mb: 64,	20✔
74	segment_cache_size_mb: 0,	20✔
75	}	20✔
76	}	20✔
77	}
78
79	/// Minimal factory to create [`VortexFormat`] instances.
80	#[derive(Default, Debug)]
81	pub struct VortexFormatFactory {
82	session: Arc<VortexSession>,
83	}
84
85	impl GetExt for VortexFormatFactory {
86	fn get_ext(&self) -> String {	18✔
87	VORTEX_FILE_EXTENSION.to_string()	18✔
88	}	18✔
89	}
90
91	impl FileFormatFactory for VortexFormatFactory {
92	#[allow(clippy::disallowed_types)]
93	fn create(	3✔
94	&self,	3✔
95	_state: &dyn Session,	3✔
96	format_options: &std::collections::HashMap<String, String>,	3✔
97	) -> DFResult<Arc<dyn FileFormat>> {	3✔
98	if !format_options.is_empty() {	3✔
99	return Err(config_datafusion_err!(	1✔
100	"Vortex tables don't support any options"	1✔
101	));	1✔
102	}	2✔
103
104	Ok(Arc::new(VortexFormat::new(self.session.clone())))	2✔
105	}	3✔
106
107	fn default(&self) -> Arc<dyn FileFormat> {	×
108	Arc::new(VortexFormat::default())	×
109	}	×
110
111	fn as_any(&self) -> &dyn Any {	×
112	self	×
113	}	×
114	}
115
116	impl Default for VortexFormat {
117	fn default() -> Self {	18✔
118	Self::new(Arc::new(VortexSession::default()))	18✔
119	}	18✔
120	}
121
122	impl VortexFormat {
123	/// Create a new instance of the [`VortexFormat`].
124	pub fn new(session: Arc<VortexSession>) -> Self {	20✔
125	let opts = VortexFormatOptions::default();	20✔
126	Self {	20✔
127	session: session.clone(),	20✔
128	file_cache: VortexFileCache::new(	20✔
129	opts.footer_cache_size_mb,	20✔
130	opts.segment_cache_size_mb,	20✔
131	session,	20✔
132	),	20✔
133	opts,	20✔
134	}	20✔
135	}	20✔
136
137	/// Return the format specific configuration
138	pub fn options(&self) -> &VortexFormatOptions {	×
139	&self.opts	×
140	}	×
141	}
142
143	#[async_trait]
144	impl FileFormat for VortexFormat {
145	fn as_any(&self) -> &dyn Any {	×
146	self	×
147	}	×
148
UNCOV 149	fn compression_type(&self) -> Option<FileCompressionType> {	×
UNCOV 150	None	×
UNCOV 151	}	×
152
153	fn get_ext(&self) -> String {	22✔
154	VORTEX_FILE_EXTENSION.to_string()	22✔
155	}	22✔
156
157	fn get_ext_with_compression(	×
158	&self,	×
159	file_compression_type: &FileCompressionType,	×
160	) -> DFResult<String> {	×
161	match file_compression_type.get_variant() {	×
UNCOV 162	CompressionTypeVariant::UNCOMPRESSED => Ok(self.get_ext()),	×
163	_ => Err(DataFusionError::Internal(	×
UNCOV 164	"Vortex does not support file level compression.".into(),	×
UNCOV 165	)),	×
166	}
UNCOV 167	}	×
168
169	async fn infer_schema(
170	&self,
171	state: &dyn Session,
172	store: &Arc<dyn ObjectStore>,
173	objects: &[ObjectMeta],
174	) -> DFResult<SchemaRef> {	4✔
175	let mut file_schemas = stream::iter(objects.iter().cloned())	2✔
176	.map(\|o\| {	2✔
177	let store = store.clone();	2✔
178	let cache = self.file_cache.clone();	2✔
179	SpawnedTask::spawn(async move {	2✔
180	let vxf = cache.try_get(&o, store).await?;	2✔
181	let inferred_schema = vxf.dtype().to_arrow_schema()?;	2✔
182	VortexResult::Ok((o.location, inferred_schema))	2✔
183	})	2✔
184	.map(\|f\| f.vortex_expect("Failed to spawn infer_schema"))	2✔
185	})	2✔
186	.buffer_unordered(state.config_options().execution.meta_fetch_concurrency)	2✔
187	.try_collect::<Vec<_>>()	2✔
188	.await	2✔
189	.map_err(\|e\| DataFusionError::Execution(format!("Failed to infer schema: {e}")))?;	2✔
190
191	// Get consistent order of schemas for `Schema::try_merge`, as some filesystems don't have deterministic listing orders
192	file_schemas.sort_by(\|(l1, _), (l2, _)\| l1.cmp(l2));	2✔
193	let file_schemas = file_schemas.into_iter().map(\|(_, schema)\| schema);	2✔
194
195	Ok(Arc::new(Schema::try_merge(file_schemas)?))	2✔
196	}	4✔
197
198	#[cfg_attr(feature = "tracing", tracing::instrument(skip_all, fields(location = object.location.as_ref()
199	)))]
200	async fn infer_stats(
201	&self,
202	_state: &dyn Session,
203	store: &Arc<dyn ObjectStore>,
204	table_schema: SchemaRef,
205	object: &ObjectMeta,
206	) -> DFResult<Statistics> {	52✔
207	let object = object.clone();	28✔
208	let store = store.clone();	28✔
209	let cache = self.file_cache.clone();	28✔
210	SpawnedTask::spawn(async move {	28✔
211	let vxf = cache.try_get(&object, store.clone()).await.map_err(\|e\| {	28✔
212	DataFusionError::Execution(format!(	×
UNCOV 213	"Failed to open Vortex file {}: {e}",	×
UNCOV 214	object.location	×
UNCOV 215	))	×
UNCOV 216	})?;	×
217
218	let struct_dtype = vxf	28✔
219	.dtype()	28✔
220	.as_struct()	28✔
221	.vortex_expect("dtype is not a struct");	28✔
222
223	// Evaluate the statistics for each column that we are able to return to DataFusion.
224	let Some(file_stats) = vxf.file_stats() else {	28✔
225	// If the file has no column stats, the best we can do is return a row count.
226	return Ok(Statistics {
227	num_rows: Precision::Exact(
228	usize::try_from(vxf.row_count())	×
229	.map_err(\|_\| vortex_err!("Row count overflow"))	×
UNCOV 230	.vortex_expect("Row count overflow"),	×
231	),
UNCOV 232	total_byte_size: Precision::Absent,	×
UNCOV 233	column_statistics: vec![ColumnStatistics::default(); struct_dtype.nfields()],	×
234	});
235	};
236
237	let stats = table_schema	28✔
238	.fields()	28✔
239	.iter()	28✔
240	.map(\|field\| struct_dtype.find(field.name()))	168✔
241	.map(\|idx\| match idx {	168✔
UNCOV 242	None => StatsSet::default(),	×
243	Some(id) => file_stats[id].clone(),	168✔
244	})	168✔
245	.collect_vec();	28✔
246
247	let total_byte_size = stats	28✔
248	.iter()	28✔
249	.map(\|stats_set\| {	168✔
250	stats_set	168✔
251	.get_as::<usize>(Stat::UncompressedSizeInBytes)	168✔
252	.unwrap_or_else(\|\| stats::Precision::inexact(0_usize))	168✔
253	})	168✔
254	.fold(stats::Precision::exact(0_usize), \|acc, stats_set\| {	168✔
255	acc.zip(stats_set).map(\|(acc, stats_set)\| acc + stats_set)	168✔
256	});	168✔
257
258	// Sum up the total byte size across all the columns.
259	let total_byte_size = total_byte_size.to_df();	28✔
260
261	let column_statistics = stats	28✔
262	.into_iter()	28✔
263	.zip(table_schema.fields().iter())	28✔
264	.map(\|(stats_set, field)\| {	168✔
265	let null_count = stats_set.get_as::<usize>(Stat::NullCount);	168✔
266	let min = stats_set	168✔
267	.get_scalar(Stat::Min, &DType::from_arrow(field.as_ref()))	168✔
268	.and_then(\|n\| n.map(\|n\| n.try_to_df().ok()).transpose());	168✔
269
270	let max = stats_set	168✔
271	.get_scalar(Stat::Max, &DType::from_arrow(field.as_ref()))	168✔
272	.and_then(\|n\| n.map(\|n\| n.try_to_df().ok()).transpose());	168✔
273
274	ColumnStatistics {
275	null_count: null_count.to_df(),	168✔
276	max_value: max.to_df(),	168✔
277	min_value: min.to_df(),	168✔
278	sum_value: Precision::Absent,	168✔
279	distinct_count: stats_set	168✔
280	.get_as::<bool>(Stat::IsConstant)	168✔
281	.and_then(\|is_constant\| {	168✔
UNCOV 282	is_constant.as_exact().map(\|_\| Precision::Exact(1))	×
UNCOV 283	})	×
284	.unwrap_or(Precision::Absent),	168✔
285	}
286	})	168✔
287	.collect::<Vec<_>>();	28✔
288
289	Ok(Statistics {
290	num_rows: Precision::Exact(
291	usize::try_from(vxf.row_count())	28✔
292	.map_err(\|_\| vortex_err!("Row count overflow"))	28✔
293	.vortex_expect("Row count overflow"),	28✔
294	),
295	total_byte_size,	28✔
296	column_statistics,	28✔
297	})
298	})	28✔
299	.await	28✔
300	.vortex_expect("Failed to spawn infer_stats")	28✔
301	}	52✔
302
303	async fn create_physical_plan(
304	&self,
305	_state: &dyn Session,
306	file_scan_config: FileScanConfig,
307	) -> DFResult<Arc<dyn ExecutionPlan>> {	360✔
308	if file_scan_config	180✔
309	.file_groups	180✔
310	.iter()	180✔
311	.flat_map(\|fg\| fg.files())	182✔
312	.any(\|f\| f.range.is_some())	182✔
313	{
314	return not_impl_err!("File level partitioning isn't implemented yet for Vortex");	×
315	}	180✔
316
317	if !file_scan_config.table_partition_cols.is_empty() {	180✔
318	return not_impl_err!("Hive style partitioning isn't implemented yet for Vortex");	×
319	}	180✔
320
321	if !file_scan_config.output_ordering.is_empty() {	180✔
UNCOV 322	return not_impl_err!("Vortex doesn't support output ordering");	×
323	}	180✔
324
325	let source = VortexSource::new(self.file_cache.clone(), self.session.metrics().clone());	180✔
326	Ok(DataSourceExec::from_data_source(	180✔
327	FileScanConfigBuilder::from(file_scan_config)	180✔
328	.with_source(Arc::new(source))	180✔
329	.build(),	180✔
330	))	180✔
331	}	360✔
332
333	async fn create_writer_physical_plan(
334	&self,
335	input: Arc<dyn ExecutionPlan>,
336	_state: &dyn Session,
337	conf: FileSinkConfig,
338	order_requirements: Option<LexRequirement>,
339	) -> DFResult<Arc<dyn ExecutionPlan>> {	4✔
340	if conf.insert_op != InsertOp::Append {	2✔
341	return not_impl_err!("Overwrites are not implemented yet for Vortex");	×
342	}	2✔
343
344	if !conf.table_partition_cols.is_empty() {	2✔
UNCOV 345	return not_impl_err!("Hive style partitioning isn't implemented yet for Vortex");	×
346	}	2✔
347
348	let schema = conf.output_schema().clone();	2✔
349	let sink = Arc::new(VortexSink::new(conf, schema));	2✔
350
351	Ok(Arc::new(DataSinkExec::new(input, sink, order_requirements)) as _)	2✔
352	}	4✔
353
354	fn file_source(&self) -> Arc<dyn FileSource> {	180✔
355	Arc::new(VortexSource::new(	180✔
356	self.file_cache.clone(),	180✔
357	VortexMetrics::default(),	180✔
358	))	180✔
359	}	180✔
360	}
361
362	#[cfg(test)]
363	mod tests {
364	use datafusion::execution::SessionStateBuilder;
365	use datafusion::prelude::SessionContext;
366	use tempfile::TempDir;
367
368	use super::*;
369	use crate::persistent::register_vortex_format_factory;
370
371	#[tokio::test]
372	async fn create_table() {	1✔
373	let dir = TempDir::new().unwrap();	1✔
374
375	let factory: VortexFormatFactory = Default::default();	1✔
376	let mut session_state_builder = SessionStateBuilder::new().with_default_features();	1✔
377	register_vortex_format_factory(factory, &mut session_state_builder);	1✔
378	let session = SessionContext::new_with_state(session_state_builder.build());	1✔
379
380	let df = session	1✔
381	.sql(&format!(	1✔
382	"CREATE EXTERNAL TABLE my_tbl \	1✔
383	(c1 VARCHAR NOT NULL, c2 INT NOT NULL) \	1✔
384	STORED AS vortex LOCATION '{}'",	1✔
385	dir.path().to_str().unwrap()	1✔
386	))	1✔
387	.await	1✔
388	.unwrap();	1✔
389
390	assert_eq!(df.count().await.unwrap(), 0);	1✔
391	}	1✔
392
393	#[tokio::test]
394	#[should_panic]
395	async fn fail_table_config() {	1✔
396	let dir = TempDir::new().unwrap();	1✔
397
398	let factory: VortexFormatFactory = Default::default();	1✔
399	let mut session_state_builder = SessionStateBuilder::new().with_default_features();	1✔
400	register_vortex_format_factory(factory, &mut session_state_builder);	1✔
401	let session = SessionContext::new_with_state(session_state_builder.build());	1✔
402
403	session	1✔
404	.sql(&format!(	1✔
405	"CREATE EXTERNAL TABLE my_tbl \	1✔
406	(c1 VARCHAR NOT NULL, c2 INT NOT NULL) \	1✔
407	STORED AS vortex LOCATION '{}' \	1✔
408	OPTIONS( some_key 'value' );",	1✔
409	dir.path().to_str().unwrap()	1✔
410	))	1✔
411	.await	1✔
412	.unwrap()	1✔
413	.collect()	1✔
414	.await	1✔
415	.unwrap();	1✔
416	}	1✔
417	}

vortex-data / vortex / 16565982454

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