chore: Update to DataFusion 46.0.0, update for API chanages

Signed-off-by: Andrew Lamb <[email protected]>

Author: alamb

.github/workflows/build.yml

@@ -20,7 +20,7 @@ jobs:
         uses: actions-rs/toolchain@v1
         with:
           profile: default
-          toolchain: '1.81'
+          toolchain: '1.82'
           override: true
 
       - name: Format
@@ -42,7 +42,7 @@ jobs:
         uses: actions-rs/toolchain@v1
         with:
           profile: default
-          toolchain: '1.81'
+          toolchain: '1.82'
           override: true
 
       - name: build and lint with clippy
@@ -79,7 +79,7 @@ jobs:
         uses: actions-rs/toolchain@v1
         with:
           profile: default
-          toolchain: '1.81'
+          toolchain: '1.82'
           override: true
 
       - name: Run tests
@@ -114,7 +114,7 @@ jobs:
         uses: actions-rs/toolchain@v1
         with:
           profile: default
-          toolchain: '1.81'
+          toolchain: '1.82'
           override: true
 
       # Install Java and Hadoop for HDFS integration tests
@@ -160,7 +160,7 @@ jobs:
         uses: actions-rs/toolchain@v1
         with:
           profile: default
-          toolchain: '1.81'
+          toolchain: '1.82'
           override: true
 
       - name: Download Lakectl

.github/workflows/codecov.yml

@@ -20,7 +20,7 @@ jobs:
         uses: actions-rs/toolchain@v1
         with:
           profile: default
-          toolchain: '1.81'
+          toolchain: '1.82'
           override: true
       - name: Install cargo-llvm-cov
         uses: taiki-e/install-action@cargo-llvm-cov

Cargo.toml

@@ -5,7 +5,7 @@ resolver = "2"
 
 [workspace.package]
 authors = ["Qingping Hou <[email protected]>"]
-rust-version = "1.81"
+rust-version = "1.82"
 keywords = ["deltalake", "delta", "datalake"]
 readme = "README.md"
 edition = "2021"
@@ -44,17 +44,16 @@ arrow-select = { version = "54" }
 object_store = { version = "0.11.2" , features = ["cloud"]}
 parquet = { version = "54" }
 
-# datafusion
-datafusion = "45"
-datafusion-expr = "45"
-datafusion-common = "45"
-datafusion-ffi = "45"
-datafusion-functions = "45"
-datafusion-functions-aggregate = "45"
-datafusion-physical-expr = "45"
-datafusion-physical-plan = "45"
-datafusion-proto = "45"
-datafusion-sql = "45"
+datafusion = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46" }
+datafusion-expr = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-common = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-ffi = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-functions = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-functions-aggregate = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-physical-expr = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-physical-plan = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-proto = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
+datafusion-sql = { git = "https://github.com/apache/arrow-datafusion.git", branch = "branch-46"  }
 
 # serde
 serde = { version = "1.0.194", features = ["derive"] }
@@ -77,4 +76,3 @@ async-trait = { version = "0.1" }
 futures = { version = "0.3" }
 tokio = { version = "1" }
 num_cpus = { version = "1" }
-

crates/core/src/delta_datafusion/expr.rs

@@ -34,7 +34,9 @@ use datafusion_common::Result as DFResult;
 use datafusion_common::{config::ConfigOptions, DFSchema, Result, ScalarValue, TableReference};
 use datafusion_expr::expr::InList;
 use datafusion_expr::planner::ExprPlanner;
-use datafusion_expr::{AggregateUDF, Between, BinaryExpr, Cast, Expr, Like, TableSource};
+use datafusion_expr::{
+    AggregateUDF, Between, BinaryExpr, Cast, Expr, Like, ScalarFunctionArgs, TableSource,
+};
 // Needed for MakeParquetArray
 use datafusion_expr::{ColumnarValue, Documentation, ScalarUDF, ScalarUDFImpl, Signature};
 use datafusion_functions::core::planner::CoreFunctionPlanner;
@@ -99,13 +101,13 @@ impl ScalarUDFImpl for MakeParquetArray {
         r_type
     }
 
-    fn invoke_batch(&self, args: &[ColumnarValue], number_rows: usize) -> Result<ColumnarValue> {
+    fn invoke_with_args(&self, args: ScalarFunctionArgs) -> Result<ColumnarValue> {
         let mut data_type = DataType::Null;
-        for arg in args {
+        for arg in &args.args {
             data_type = arg.data_type();
         }
 
-        match self.actual.invoke_batch(args, number_rows)? {
+        match self.actual.invoke_with_args(args)? {
             ColumnarValue::Scalar(ScalarValue::List(df_array)) => {
                 let field = Arc::new(Field::new("element", data_type, true));
                 let result = Ok(ColumnarValue::Scalar(ScalarValue::List(Arc::new(

crates/core/src/delta_datafusion/mod.rs

@@ -39,9 +39,8 @@ use async_trait::async_trait;
 use chrono::{DateTime, TimeZone, Utc};
 use datafusion::catalog::{Session, TableProviderFactory};
 use datafusion::config::TableParquetOptions;
-use datafusion::datasource::physical_plan::parquet::ParquetExecBuilder;
 use datafusion::datasource::physical_plan::{
-    wrap_partition_type_in_dict, wrap_partition_value_in_dict, FileScanConfig,
+    wrap_partition_type_in_dict, wrap_partition_value_in_dict, FileScanConfig, ParquetSource,
 };
 use datafusion::datasource::{listing::PartitionedFile, MemTable, TableProvider, TableType};
 use datafusion::execution::context::{SessionConfig, SessionContext, SessionState, TaskContext};
@@ -648,36 +647,39 @@ impl<'a> DeltaScanBuilder<'a> {
             ..Default::default()
         };
 
-        let mut exec_plan_builder = ParquetExecBuilder::new(
-            FileScanConfig::new(self.log_store.object_store_url(), file_schema)
-                .with_file_groups(
-                    // If all files were filtered out, we still need to emit at least one partition to
-                    // pass datafusion sanity checks.
-                    //
-                    // See https://github.com/apache/datafusion/issues/11322
-                    if file_groups.is_empty() {
-                        vec![vec![]]
-                    } else {
-                        file_groups.into_values().collect()
-                    },
-                )
-                .with_statistics(stats)
-                .with_projection(self.projection.cloned())
-                .with_limit(self.limit)
-                .with_table_partition_cols(table_partition_cols),
-        )
-        .with_schema_adapter_factory(Arc::new(DeltaSchemaAdapterFactory {}))
-        .with_table_parquet_options(parquet_options);
+        let mut file_source = ParquetSource::new(parquet_options)
+            .with_schema_adapter_factory(Arc::new(DeltaSchemaAdapterFactory {}));
 
         // Sometimes (i.e Merge) we want to prune files that don't make the
         // filter and read the entire contents for files that do match the
         // filter
         if let Some(predicate) = logical_filter {
             if config.enable_parquet_pushdown {
-                exec_plan_builder = exec_plan_builder.with_predicate(predicate);
+                file_source = file_source.with_predicate(Arc::clone(&file_schema), predicate);
             }
         };
 
+        let file_scan_config = FileScanConfig::new(
+            self.log_store.object_store_url(),
+            file_schema,
+            Arc::new(file_source),
+        )
+        .with_file_groups(
+            // If all files were filtered out, we still need to emit at least one partition to
+            // pass datafusion sanity checks.
+            //
+            // See https://github.com/apache/datafusion/issues/11322
+            if file_groups.is_empty() {
+                vec![vec![]]
+            } else {
+                file_groups.into_values().collect()
+            },
+        )
+        .with_statistics(stats)
+        .with_projection(self.projection.cloned())
+        .with_limit(self.limit)
+        .with_table_partition_cols(table_partition_cols);
+
         let metrics = ExecutionPlanMetricsSet::new();
         MetricBuilder::new(&metrics)
             .global_counter("files_scanned")
@@ -688,7 +690,7 @@ impl<'a> DeltaScanBuilder<'a> {
 
         Ok(DeltaScan {
             table_uri: ensure_table_uri(self.log_store.root_uri())?.as_str().into(),
-            parquet_scan: exec_plan_builder.build_arc(),
+            parquet_scan: file_scan_config.build(),
             config,
             logical_schema,
             metrics,
@@ -1960,7 +1962,7 @@ mod tests {
     use bytes::Bytes;
     use chrono::{TimeZone, Utc};
     use datafusion::assert_batches_sorted_eq;
-    use datafusion::datasource::physical_plan::ParquetExec;
+    use datafusion::datasource::source::DataSourceExec;
     use datafusion::physical_plan::empty::EmptyExec;
     use datafusion::physical_plan::{visit_execution_plan, ExecutionPlanVisitor, PhysicalExpr};
     use datafusion_expr::lit;
@@ -2713,7 +2715,7 @@ mod tests {
             .await
             .unwrap();
 
-        let mut visitor = ParquetPredicateVisitor::default();
+        let mut visitor = ParquetVisitor::default();
         visit_execution_plan(&scan, &mut visitor).unwrap();
 
         assert_eq!(visitor.predicate.unwrap().to_string(), "a@0 = s");
@@ -2748,7 +2750,7 @@ mod tests {
             .await
             .unwrap();
 
-        let mut visitor = ParquetPredicateVisitor::default();
+        let mut visitor = ParquetVisitor::default();
         visit_execution_plan(&scan, &mut visitor).unwrap();
 
         assert!(visitor.predicate.is_none());
@@ -2777,42 +2779,46 @@ mod tests {
             .await
             .unwrap();
 
-        let mut visitor = ParquetOptionsVisitor::default();
+        let mut visitor = ParquetVisitor::default();
         visit_execution_plan(&scan, &mut visitor).unwrap();
 
         assert_eq!(ctx.copied_table_options().parquet, visitor.options.unwrap());
     }
 
+    /// Extracts fields from the parquet scan
     #[derive(Default)]
-    struct ParquetPredicateVisitor {
+    struct ParquetVisitor {
         predicate: Option<Arc<dyn PhysicalExpr>>,
         pruning_predicate: Option<Arc<PruningPredicate>>,
+        options: Option<TableParquetOptions>,
     }
 
-    impl ExecutionPlanVisitor for ParquetPredicateVisitor {
+    impl ExecutionPlanVisitor for ParquetVisitor {
         type Error = DataFusionError;
 
         fn pre_visit(&mut self, plan: &dyn ExecutionPlan) -> Result<bool, Self::Error> {
-            if let Some(parquet_exec) = plan.as_any().downcast_ref::<ParquetExec>() {
-                self.predicate = parquet_exec.predicate().cloned();
-                self.pruning_predicate = parquet_exec.pruning_predicate().cloned();
-            }
-            Ok(true)
-        }
-    }
-
-    #[derive(Default)]
-    struct ParquetOptionsVisitor {
-        options: Option<TableParquetOptions>,
-    }
+            let Some(datasource_exec) = plan.as_any().downcast_ref::<DataSourceExec>() else {
+                return Ok(true);
+            };
 
-    impl ExecutionPlanVisitor for ParquetOptionsVisitor {
-        type Error = DataFusionError;
+            let Some(scan_config) = datasource_exec
+                .data_source()
+                .as_any()
+                .downcast_ref::<FileScanConfig>()
+            else {
+                return Ok(true);
+            };
 
-        fn pre_visit(&mut self, plan: &dyn ExecutionPlan) -> Result<bool, Self::Error> {
-            if let Some(parquet_exec) = plan.as_any().downcast_ref::<ParquetExec>() {
-                self.options = Some(parquet_exec.table_parquet_options().clone())
+            if let Some(parquet_source) = scan_config
+                .file_source
+                .as_any()
+                .downcast_ref::<ParquetSource>()
+            {
+                self.options = Some(parquet_source.table_parquet_options().clone());
+                self.predicate = parquet_source.predicate().cloned();
+                self.pruning_predicate = parquet_source.pruning_predicate().cloned();
             }
+
             Ok(true)
         }
     }

crates/core/src/operations/load_cdf.rs

@@ -16,11 +16,10 @@ use std::time::SystemTime;
 use arrow_array::RecordBatch;
 use arrow_schema::{ArrowError, Field, Schema};
 use chrono::{DateTime, Utc};
-use datafusion::datasource::file_format::parquet::ParquetFormat;
-use datafusion::datasource::file_format::FileFormat;
-use datafusion::datasource::physical_plan::FileScanConfig;
+use datafusion::datasource::physical_plan::{FileScanConfig, FileSource, ParquetSource};
 use datafusion::execution::SessionState;
 use datafusion::prelude::SessionContext;
+use datafusion_common::config::TableParquetOptions;
 use datafusion_common::ScalarValue;
 use datafusion_physical_expr::{expressions, PhysicalExpr};
 use datafusion_physical_plan::projection::ProjectionExec;
@@ -369,38 +368,38 @@ impl CdfLoadBuilder {
         )?;
 
         // Create the parquet scans for each associated type of file.
-        let cdc_scan = ParquetFormat::new()
-            .create_physical_plan(
-                session_sate,
-                FileScanConfig::new(self.log_store.object_store_url(), cdc_file_schema)
-                    .with_file_groups(cdc_file_groups.into_values().collect())
-                    .with_table_partition_cols(cdc_partition_cols),
-                filters,
-            )
-            .await?;
-
-        let add_scan = ParquetFormat::new()
-            .create_physical_plan(
-                session_sate,
-                FileScanConfig::new(
-                    self.log_store.object_store_url(),
-                    add_remove_file_schema.clone(),
-                )
-                .with_file_groups(add_file_groups.into_values().collect())
-                .with_table_partition_cols(add_remove_partition_cols.clone()),
-                filters,
-            )
-            .await?;
-
-        let remove_scan = ParquetFormat::new()
-            .create_physical_plan(
-                session_sate,
-                FileScanConfig::new(self.log_store.object_store_url(), add_remove_file_schema)
-                    .with_file_groups(remove_file_groups.into_values().collect())
-                    .with_table_partition_cols(add_remove_partition_cols),
-                filters,
-            )
-            .await?;
+        let mut parquet_source = ParquetSource::new(TableParquetOptions::new());
+        if let Some(filters) = filters {
+            parquet_source =
+                parquet_source.with_predicate(Arc::clone(&cdc_file_schema), Arc::clone(filters));
+        }
+        let parquet_source: Arc<dyn FileSource> = Arc::new(parquet_source);
+        let cdc_scan: Arc<dyn ExecutionPlan> = FileScanConfig::new(
+            self.log_store.object_store_url(),
+            Arc::clone(&cdc_file_schema),
+            Arc::clone(&parquet_source),
+        )
+        .with_file_groups(cdc_file_groups.into_values().collect())
+        .with_table_partition_cols(cdc_partition_cols)
+        .build();
+
+        let add_scan: Arc<dyn ExecutionPlan> = FileScanConfig::new(
+            self.log_store.object_store_url(),
+            Arc::clone(&add_remove_file_schema),
+            Arc::clone(&parquet_source),
+        )
+        .with_file_groups(add_file_groups.into_values().collect())
+        .with_table_partition_cols(add_remove_partition_cols.clone())
+        .build();
+
+        let remove_scan: Arc<dyn ExecutionPlan> = FileScanConfig::new(
+            self.log_store.object_store_url(),
+            Arc::clone(&add_remove_file_schema),
+            parquet_source,
+        )
+        .with_file_groups(remove_file_groups.into_values().collect())
+        .with_table_partition_cols(add_remove_partition_cols)
+        .build();
 
         // The output batches are then unioned to create a single output. Coalesce partitions is only here for the time
         // being for development. I plan to parallelize the reads once the base idea is correct.