perf: count(*) for append-only tables

src/common/query/Cargo.toml

@@ -12,6 +12,7 @@ workspace = true
 
 [dependencies]
 api.workspace = true
+arrow-schema.workspace = true
 async-trait.workspace = true
 bytes.workspace = true
 common-error.workspace = true
@@ -21,6 +22,7 @@ common-time.workspace = true
 datafusion.workspace = true
 datafusion-common.workspace = true
 datafusion-expr.workspace = true
+datafusion-physical-expr.workspace = true
 datatypes.workspace = true
 serde.workspace = true
 snafu.workspace = true
@@ -31,4 +33,5 @@ store-api.workspace = true
 
 [dev-dependencies]
 common-base.workspace = true
+futures-util.workspace = true
 tokio.workspace = true

src/common/query/src/lib.rs

@@ -19,8 +19,10 @@ pub mod logical_plan;
 pub mod prelude;
 pub mod request;
 mod signature;
+pub mod stream;
 #[cfg(any(test, feature = "testing"))]
 pub mod test_util;
+
 use std::fmt::{Debug, Display, Formatter};
 use std::sync::Arc;
 

src/common/query/src/stream.rs

@@ -0,0 +1,175 @@
+// Copyright 2023 Greptime Team
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+use std::any::Any;
+use std::fmt::{Debug, Formatter};
+use std::sync::{Arc, Mutex};
+
+use arrow_schema::SchemaRef as ArrowSchemaRef;
+use common_recordbatch::adapter::DfRecordBatchStreamAdapter;
+use common_recordbatch::SendableRecordBatchStream;
+use datafusion::execution::context::TaskContext;
+use datafusion::execution::SendableRecordBatchStream as DfSendableRecordBatchStream;
+use datafusion::physical_plan::{
+    DisplayAs, DisplayFormatType, ExecutionMode, ExecutionPlan, PlanProperties,
+};
+use datafusion_common::DataFusionError;
+use datafusion_physical_expr::{EquivalenceProperties, Partitioning, PhysicalSortExpr};
+use datatypes::schema::SchemaRef;
+
+/// Adapts greptime's [SendableRecordBatchStream] to DataFusion's [ExecutionPlan].
+pub struct StreamScanAdapter {
+    stream: Mutex<Option<SendableRecordBatchStream>>,
+    schema: SchemaRef,
+    arrow_schema: ArrowSchemaRef,
+    properties: PlanProperties,
+    output_ordering: Option<Vec<PhysicalSortExpr>>,
+}
+
+impl Debug for StreamScanAdapter {
+    fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
+        f.debug_struct("StreamScanAdapter")
+            .field("stream", &"<SendableRecordBatchStream>")
+            .field("schema", &self.schema)
+            .finish()
+    }
+}
+
+impl StreamScanAdapter {
+    pub fn new(stream: SendableRecordBatchStream) -> Self {
+        let schema = stream.schema();
+        let arrow_schema = schema.arrow_schema().clone();
+        let properties = PlanProperties::new(
+            EquivalenceProperties::new(arrow_schema.clone()),
+            Partitioning::UnknownPartitioning(1),
+            ExecutionMode::Bounded,
+        );
+
+        Self {
+            stream: Mutex::new(Some(stream)),
+            schema,
+            arrow_schema,
+            properties,
+            output_ordering: None,
+        }
+    }
+
+    pub fn with_output_ordering(mut self, output_ordering: Option<Vec<PhysicalSortExpr>>) -> Self {
+        self.output_ordering = output_ordering;
+        self
+    }
+}
+
+impl DisplayAs for StreamScanAdapter {
+    fn fmt_as(&self, _t: DisplayFormatType, f: &mut Formatter) -> std::fmt::Result {
+        write!(
+            f,
+            "StreamScanAdapter: [<SendableRecordBatchStream>], schema: ["
+        )?;
+        write!(f, "{:?}", &self.arrow_schema)?;
+        write!(f, "]")
+    }
+}
+
+impl ExecutionPlan for StreamScanAdapter {
+    fn as_any(&self) -> &dyn Any {
+        self
+    }
+
+    fn schema(&self) -> ArrowSchemaRef {
+        self.arrow_schema.clone()
+    }
+
+    fn properties(&self) -> &PlanProperties {
+        &self.properties
+    }
+
+    fn children(&self) -> Vec<&Arc<dyn ExecutionPlan>> {
+        vec![]
+    }
+
+    // DataFusion will swap children unconditionally.
+    // But since this node is leaf node, it's safe to just return self.
+    fn with_new_children(
+        self: Arc<Self>,
+        _children: Vec<Arc<dyn ExecutionPlan>>,
+    ) -> datafusion_common::Result<Arc<dyn ExecutionPlan>> {
+        Ok(self.clone())
+    }
+
+    fn execute(
+        &self,
+        _partition: usize,
+        _context: Arc<TaskContext>,
+    ) -> datafusion_common::Result<DfSendableRecordBatchStream> {
+        let mut stream = self.stream.lock().unwrap();
+        let stream = stream
+            .take()
+            .ok_or_else(|| DataFusionError::Execution("Stream already exhausted".to_string()))?;
+        Ok(Box::pin(DfRecordBatchStreamAdapter::new(stream)))
+    }
+}
+
+#[cfg(test)]
+mod test {
+    use common_recordbatch::{RecordBatch, RecordBatches};
+    use datafusion::prelude::SessionContext;
+    use datatypes::data_type::ConcreteDataType;
+    use datatypes::schema::{ColumnSchema, Schema};
+    use datatypes::vectors::Int32Vector;
+    use futures_util::TryStreamExt;
+
+    use super::*;
+
+    #[tokio::test]
+    async fn test_simple_table_scan() {
+        let ctx = SessionContext::new();
+        let schema = Arc::new(Schema::new(vec![ColumnSchema::new(
+            "a",
+            ConcreteDataType::int32_datatype(),
+            false,
+        )]));
+
+        let batch1 = RecordBatch::new(
+            schema.clone(),
+            vec![Arc::new(Int32Vector::from_slice([1, 2])) as _],
+        )
+        .unwrap();
+        let batch2 = RecordBatch::new(
+            schema.clone(),
+            vec![Arc::new(Int32Vector::from_slice([3, 4, 5])) as _],
+        )
+        .unwrap();
+
+        let recordbatches =
+            RecordBatches::try_new(schema.clone(), vec![batch1.clone(), batch2.clone()]).unwrap();
+        let stream = recordbatches.as_stream();
+
+        let scan = StreamScanAdapter::new(stream);
+
+        assert_eq!(scan.schema(), schema.arrow_schema().clone());
+
+        let stream = scan.execute(0, ctx.task_ctx()).unwrap();
+        let recordbatches = stream.try_collect::<Vec<_>>().await.unwrap();
+        assert_eq!(recordbatches[0], batch1.into_df_record_batch());
+        assert_eq!(recordbatches[1], batch2.into_df_record_batch());
+
+        let result = scan.execute(0, ctx.task_ctx());
+        assert!(result.is_err());
+        match result {
+            Err(e) => assert!(e.to_string().contains("Stream already exhausted")),
+            _ => unreachable!(),
+        }
+    }
+}

src/file-engine/src/engine.rs

@@ -90,7 +90,8 @@ impl RegionEngine for FileRegionEngine {
         request: ScanRequest,
     ) -> Result<RegionScannerRef, BoxedError> {
         let stream = self.handle_query(region_id, request).await?;
-        let scanner = Box::new(SinglePartitionScanner::new(stream));
+        // We don't support enabling append mode for file engine.
+        let scanner = Box::new(SinglePartitionScanner::new(stream, false));
         Ok(scanner)
     }
 

src/mito2/src/memtable.rs

@@ -69,6 +69,8 @@ pub struct MemtableStats {
     /// The time range that this memtable contains. It is None if
     /// and only if the memtable is empty.
     time_range: Option<(Timestamp, Timestamp)>,
+    /// Total rows in memtable
+    num_rows: usize,
 }
 
 impl MemtableStats {
@@ -88,6 +90,11 @@ impl MemtableStats {
     pub fn time_range(&self) -> Option<(Timestamp, Timestamp)> {
         self.time_range
     }
+
+    /// Returns the num of total rows in memtable.
+    pub fn num_rows(&self) -> usize {
+        self.num_rows
+    }
 }
 
 pub type BoxedBatchIterator = Box<dyn Iterator<Item = Result<Batch>> + Send>;

src/mito2/src/memtable/partition_tree.rs

@@ -25,7 +25,7 @@ mod shard_builder;
 mod tree;
 
 use std::fmt;
-use std::sync::atomic::{AtomicI64, Ordering};
+use std::sync::atomic::{AtomicI64, AtomicUsize, Ordering};
 use std::sync::Arc;
 
 use common_base::readable_size::ReadableSize;
@@ -114,6 +114,7 @@ pub struct PartitionTreeMemtable {
     alloc_tracker: AllocTracker,
     max_timestamp: AtomicI64,
     min_timestamp: AtomicI64,
+    num_rows: AtomicUsize,
 }
 
 impl fmt::Debug for PartitionTreeMemtable {
@@ -139,6 +140,7 @@ impl Memtable for PartitionTreeMemtable {
 
         self.update_stats(&metrics);
 
+        self.num_rows.fetch_add(kvs.num_rows(), Ordering::Relaxed);
         res
     }
 
@@ -150,6 +152,7 @@ impl Memtable for PartitionTreeMemtable {
 
         self.update_stats(&metrics);
 
+        self.num_rows.fetch_add(1, Ordering::Relaxed);
         res
     }
 
@@ -202,6 +205,7 @@ impl Memtable for PartitionTreeMemtable {
             return MemtableStats {
                 estimated_bytes,
                 time_range: None,
+                num_rows: 0,
             };
         }
 
@@ -219,6 +223,7 @@ impl Memtable for PartitionTreeMemtable {
         MemtableStats {
             estimated_bytes,
             time_range: Some((min_timestamp, max_timestamp)),
+            num_rows: self.num_rows.load(Ordering::Relaxed),
         }
     }
 
@@ -256,6 +261,7 @@ impl PartitionTreeMemtable {
             alloc_tracker,
             max_timestamp: AtomicI64::new(i64::MIN),
             min_timestamp: AtomicI64::new(i64::MAX),
+            num_rows: AtomicUsize::new(0),
         }
     }
 

src/mito2/src/memtable/time_series.rs

@@ -15,7 +15,7 @@
 use std::collections::btree_map::Entry;
 use std::collections::{BTreeMap, Bound, HashSet};
 use std::fmt::{Debug, Formatter};
-use std::sync::atomic::{AtomicI64, Ordering};
+use std::sync::atomic::{AtomicI64, AtomicUsize, Ordering};
 use std::sync::{Arc, RwLock};
 use std::time::{Duration, Instant};
 
@@ -101,6 +101,7 @@ pub struct TimeSeriesMemtable {
     min_timestamp: AtomicI64,
     dedup: bool,
     merge_mode: MergeMode,
+    num_rows: AtomicUsize,
 }
 
 impl TimeSeriesMemtable {
@@ -133,6 +134,7 @@ impl TimeSeriesMemtable {
             min_timestamp: AtomicI64::new(i64::MAX),
             dedup,
             merge_mode,
+            num_rows: Default::default(),
         }
     }
 
@@ -232,6 +234,8 @@ impl Memtable for TimeSeriesMemtable {
         // We may lift the primary key length check out of Memtable::write
         // so that we can ensure writing to memtable will succeed.
         self.update_stats(local_stats);
+
+        self.num_rows.fetch_add(kvs.num_rows(), Ordering::Relaxed);
         Ok(())
     }
 
@@ -241,6 +245,7 @@ impl Memtable for TimeSeriesMemtable {
         local_stats.allocated += std::mem::size_of::<Timestamp>() + std::mem::size_of::<OpType>();
 
         self.update_stats(local_stats);
+        self.num_rows.fetch_add(1, Ordering::Relaxed);
         res
     }
 
@@ -320,6 +325,7 @@ impl Memtable for TimeSeriesMemtable {
             return MemtableStats {
                 estimated_bytes,
                 time_range: None,
+                num_rows: 0,
             };
         }
         let ts_type = self
@@ -335,6 +341,7 @@ impl Memtable for TimeSeriesMemtable {
         MemtableStats {
             estimated_bytes,
             time_range: Some((min_timestamp, max_timestamp)),
+            num_rows: self.num_rows.load(Ordering::Relaxed),
         }
     }
 

src/mito2/src/read/scan_region.rs

@@ -697,6 +697,12 @@ impl ScanInput {
             }
         });
     }
+
+    pub(crate) fn total_rows(&self) -> usize {
+        let rows_in_files: usize = self.files.iter().map(|f| f.num_rows()).sum();
+        let rows_in_memtables: usize = self.memtables.iter().map(|m| m.stats().num_rows()).sum();
+        rows_in_files + rows_in_memtables
+    }
 }
 
 #[cfg(test)]

src/mito2/src/read/seq_scan.rs

@@ -65,7 +65,11 @@ impl SeqScan {
     /// Creates a new [SeqScan].
     pub(crate) fn new(input: ScanInput) -> Self {
         let parallelism = input.parallelism.parallelism.max(1);
-        let properties = ScannerProperties::new_with_partitions(parallelism);
+        let properties = ScannerProperties {
+            partitions: vec![vec![]; parallelism],
+            append_mode: input.append_mode,
+            total_rows: input.total_rows(),
+        };
         let stream_ctx = Arc::new(StreamContext::new(input));
 
         Self {