feat: strategized plan compaction

rust/lance/src/dataset/optimize.rs

@@ -205,9 +205,157 @@ impl AddAssign for CompactionMetrics {
     }
 }
 
+/// Trait for implementing custom compaction planning strategies.
+///
+/// This trait allows users to define their own compaction strategies by implementing
+/// the `plan` method. The default implementation is provided by [`DefaultCompactionPlanner`].
+#[async_trait::async_trait]
+pub trait CompactionPlanner: Send + Sync {
+    // get all fragments by default
+    fn get_fragments(&self, dataset: &Dataset, _options: &CompactionOptions) -> Vec<FileFragment> {
+        // get_fragments should be returning fragments in sorted order (by id)
+        // and fragment ids should be unique
+        dataset.get_fragments()
+    }
+
+    // no filter by default
+    async fn filter_fragments(
+        &self,
+        _dataset: &Dataset,
+        fragments: Vec<FileFragment>,
+        _options: &CompactionOptions,
+    ) -> Result<Vec<FileFragment>> {
+        Ok(fragments)
+    }
+
+    async fn plan(&self, dataset: &Dataset, options: &CompactionOptions) -> Result<CompactionPlan>;
+}
+
+/// Formulate a plan to compact the files in a dataset
+///
+/// The compaction plan will contain a list of tasks to execute. Each task
+/// will contain approximately `target_rows_per_fragment` rows and will be
+/// rewriting fragments that are adjacent in the dataset's fragment list. Some
+/// tasks may contain a single fragment when that fragment has deletions that
+/// are being materialized and doesn't have any neighbors that need to be
+/// compacted.
+#[derive(Debug, Clone, Default)]
+pub struct DefaultCompactionPlanner;
+
+#[async_trait::async_trait]
+impl CompactionPlanner for DefaultCompactionPlanner {
+    async fn plan(&self, dataset: &Dataset, options: &CompactionOptions) -> Result<CompactionPlan> {
+        let fragments = self.get_fragments(dataset, options);
+        debug_assert!(
+            fragments.windows(2).all(|w| w[0].id() < w[1].id()),
+            "fragments in manifest are not sorted"
+        );
+        let mut fragment_metrics = futures::stream::iter(fragments)
+            .map(|fragment| async move {
+                match collect_metrics(&fragment).await {
+                    Ok(metrics) => Ok((fragment.metadata, metrics)),
+                    Err(e) => Err(e),
+                }
+            })
+            .buffered(dataset.object_store().io_parallelism());
+
+        let index_fragmaps = load_index_fragmaps(dataset).await?;
+        let indices_containing_frag = |frag_id: u32| {
+            index_fragmaps
+                .iter()
+                .enumerate()
+                .filter(|(_, bitmap)| bitmap.contains(frag_id))
+                .map(|(pos, _)| pos)
+                .collect::<Vec<_>>()
+        };
+
+        let mut candidate_bins: Vec<CandidateBin> = Vec::new();
+        let mut current_bin: Option<CandidateBin> = None;
+        let mut i = 0;
+
+        while let Some(res) = fragment_metrics.next().await {
+            let (fragment, metrics) = res?;
+
+            let candidacy = if options.materialize_deletions
+                && metrics.deletion_percentage() > options.materialize_deletions_threshold
+            {
+                Some(CompactionCandidacy::CompactItself)
+            } else if metrics.physical_rows < options.target_rows_per_fragment {
+                // Only want to compact if their are neighbors to compact such that
+                // we can get a larger fragment.
+                Some(CompactionCandidacy::CompactWithNeighbors)
+            } else {
+                // Not a candidate
+                None
+            };
+
+            let indices = indices_containing_frag(fragment.id as u32);
+
+            match (candidacy, &mut current_bin) {
+                (None, None) => {} // keep searching
+                (Some(candidacy), None) => {
+                    // Start a new bin
+                    current_bin = Some(CandidateBin {
+                        fragments: vec![fragment],
+                        pos_range: i..(i + 1),
+                        candidacy: vec![candidacy],
+                        row_counts: vec![metrics.num_rows()],
+                        indices,
+                    });
+                }
+                (Some(candidacy), Some(bin)) => {
+                    // We cannot mix "indexed" and "non-indexed" fragments and so we only consider
+                    // the existing bin if it contains the same indices
+                    if bin.indices == indices {
+                        // Add to current bin
+                        bin.fragments.push(fragment);
+                        bin.pos_range.end += 1;
+                        bin.candidacy.push(candidacy);
+                        bin.row_counts.push(metrics.num_rows());
+                    } else {
+                        // Index set is different.  Complete previous bin and start new one
+                        candidate_bins.push(current_bin.take().unwrap());
+                        current_bin = Some(CandidateBin {
+                            fragments: vec![fragment],
+                            pos_range: i..(i + 1),
+                            candidacy: vec![candidacy],
+                            row_counts: vec![metrics.num_rows()],
+                            indices,
+                        });
+                    }
+                }
+                (None, Some(_)) => {
+                    // Bin is complete
+                    candidate_bins.push(current_bin.take().unwrap());
+                }
+            }
+
+            i += 1;
+        }
+
+        // Flush the last bin
+        if let Some(bin) = current_bin {
+            candidate_bins.push(bin);
+        }
+
+        let final_bins = candidate_bins
+            .into_iter()
+            .filter(|bin| !bin.is_noop())
+            .flat_map(|bin| bin.split_for_size(options.target_rows_per_fragment))
+            .map(|bin| TaskData {
+                fragments: bin.fragments,
+            });
+
+        let mut compaction_plan = CompactionPlan::new(dataset.manifest.version, options.clone());
+        compaction_plan.extend_tasks(final_bins);
+
+        Ok(compaction_plan)
+    }
+}
+
 /// Compacts the files in the dataset without reordering them.
 ///
-/// This does a few things:
+/// By default, his does a few things:
 ///  * Removes deleted rows from fragments.
 ///  * Removes dropped columns from fragments.
 ///  * Merges fragments that are too small.
@@ -216,14 +364,24 @@ impl AddAssign for CompactionMetrics {
 ///
 /// If no compaction is needed, this method will not make a new version of the table.
 pub async fn compact_files(
+    dataset: &mut Dataset,
+    options: CompactionOptions,
+    remap_options: Option<Arc<dyn IndexRemapperOptions>>, // These will be deprecated later
+) -> Result<CompactionMetrics> {
+    let planner = DefaultCompactionPlanner;
+    compact_files_with_planner(dataset, options, remap_options, &planner).await
+}
+
+pub async fn compact_files_with_planner(
     dataset: &mut Dataset,
     mut options: CompactionOptions,
     remap_options: Option<Arc<dyn IndexRemapperOptions>>, // These will be deprecated later
+    planner: &dyn CompactionPlanner,
 ) -> Result<CompactionMetrics> {
     info!(target: TRACE_DATASET_EVENTS, event=DATASET_COMPACTING_EVENT, uri = &dataset.uri);
     options.validate();
 
-    let compaction_plan: CompactionPlan = plan_compaction(dataset, &options).await?;
+    let compaction_plan: CompactionPlan = planner.plan(dataset, &options).await?;
 
     // If nothing to compact, don't make a commit.
     if compaction_plan.tasks().is_empty() {
@@ -457,125 +615,12 @@ async fn load_index_fragmaps(dataset: &Dataset) -> Result<Vec<RoaringBitmap>> {
     Ok(index_fragmaps)
 }
 
-/// Formulate a plan to compact the files in a dataset
-///
-/// The compaction plan will contain a list of tasks to execute. Each task
-/// will contain approximately `target_rows_per_fragment` rows and will be
-/// rewriting fragments that are adjacent in the dataset's fragment list. Some
-/// tasks may contain a single fragment when that fragment has deletions that
-/// are being materialized and doesn't have any neighbors that need to be
-/// compacted.
 pub async fn plan_compaction(
     dataset: &Dataset,
     options: &CompactionOptions,
 ) -> Result<CompactionPlan> {
-    // get_fragments should be returning fragments in sorted order (by id)
-    // and fragment ids should be unique
-    let fragments = dataset.get_fragments();
-    debug_assert!(
-        fragments.windows(2).all(|w| w[0].id() < w[1].id()),
-        "fragments in manifest are not sorted"
-    );
-    let mut fragment_metrics = futures::stream::iter(fragments)
-        .map(|fragment| async move {
-            match collect_metrics(&fragment).await {
-                Ok(metrics) => Ok((fragment.metadata, metrics)),
-                Err(e) => Err(e),
-            }
-        })
-        .buffered(dataset.object_store().io_parallelism());
-
-    let index_fragmaps = load_index_fragmaps(dataset).await?;
-    let indices_containing_frag = |frag_id: u32| {
-        index_fragmaps
-            .iter()
-            .enumerate()
-            .filter(|(_, bitmap)| bitmap.contains(frag_id))
-            .map(|(pos, _)| pos)
-            .collect::<Vec<_>>()
-    };
-
-    let mut candidate_bins: Vec<CandidateBin> = Vec::new();
-    let mut current_bin: Option<CandidateBin> = None;
-    let mut i = 0;
-
-    while let Some(res) = fragment_metrics.next().await {
-        let (fragment, metrics) = res?;
-
-        let candidacy = if options.materialize_deletions
-            && metrics.deletion_percentage() > options.materialize_deletions_threshold
-        {
-            Some(CompactionCandidacy::CompactItself)
-        } else if metrics.physical_rows < options.target_rows_per_fragment {
-            // Only want to compact if their are neighbors to compact such that
-            // we can get a larger fragment.
-            Some(CompactionCandidacy::CompactWithNeighbors)
-        } else {
-            // Not a candidate
-            None
-        };
-
-        let indices = indices_containing_frag(fragment.id as u32);
-
-        match (candidacy, &mut current_bin) {
-            (None, None) => {} // keep searching
-            (Some(candidacy), None) => {
-                // Start a new bin
-                current_bin = Some(CandidateBin {
-                    fragments: vec![fragment],
-                    pos_range: i..(i + 1),
-                    candidacy: vec![candidacy],
-                    row_counts: vec![metrics.num_rows()],
-                    indices,
-                });
-            }
-            (Some(candidacy), Some(bin)) => {
-                // We cannot mix "indexed" and "non-indexed" fragments and so we only consider
-                // the existing bin if it contains the same indices
-                if bin.indices == indices {
-                    // Add to current bin
-                    bin.fragments.push(fragment);
-                    bin.pos_range.end += 1;
-                    bin.candidacy.push(candidacy);
-                    bin.row_counts.push(metrics.num_rows());
-                } else {
-                    // Index set is different.  Complete previous bin and start new one
-                    candidate_bins.push(current_bin.take().unwrap());
-                    current_bin = Some(CandidateBin {
-                        fragments: vec![fragment],
-                        pos_range: i..(i + 1),
-                        candidacy: vec![candidacy],
-                        row_counts: vec![metrics.num_rows()],
-                        indices,
-                    });
-                }
-            }
-            (None, Some(_)) => {
-                // Bin is complete
-                candidate_bins.push(current_bin.take().unwrap());
-            }
-        }
-
-        i += 1;
-    }
-
-    // Flush the last bin
-    if let Some(bin) = current_bin {
-        candidate_bins.push(bin);
-    }
-
-    let final_bins = candidate_bins
-        .into_iter()
-        .filter(|bin| !bin.is_noop())
-        .flat_map(|bin| bin.split_for_size(options.target_rows_per_fragment))
-        .map(|bin| TaskData {
-            fragments: bin.fragments,
-        });
-
-    let mut compaction_plan = CompactionPlan::new(dataset.manifest.version, options.clone());
-    compaction_plan.extend_tasks(final_bins);
-
-    Ok(compaction_plan)
+    let planner = DefaultCompactionPlanner;
+    planner.plan(dataset, options).await
 }
 
 /// The result of a single compaction task.
@@ -3519,4 +3564,37 @@ mod tests {
             plan
         );
     }
+
+    #[tokio::test]
+    async fn test_default_compaction_planner() {
+        let test_dir = TempStrDir::default();
+        let test_uri = &test_dir;
+
+        let data = sample_data();
+        let schema = data.schema();
+
+        // Create dataset with multiple small fragments
+        let reader = RecordBatchIterator::new(vec![Ok(data.clone())], schema.clone());
+        let write_params = WriteParams {
+            max_rows_per_file: 2000,
+            ..Default::default()
+        };
+        let dataset = Dataset::write(reader, test_uri, Some(write_params))
+            .await
+            .unwrap();
+
+        assert_eq!(dataset.get_fragments().len(), 5);
+
+        // Test default planner
+        let planner = DefaultCompactionPlanner;
+        let options = CompactionOptions {
+            target_rows_per_fragment: 5000,
+            ..Default::default()
+        };
+        let plan = planner.plan(&dataset, &options).await.unwrap();
+
+        // Should create tasks to compact small fragments
+        assert!(!plan.tasks.is_empty());
+        assert_eq!(plan.read_version, dataset.manifest.version);
+    }
 }