Struct Compactor

pub struct Compactor<K, V, T, D> {
    cfg: PersistConfig,
    metrics: Arc<Metrics>,
    sender: Sender<(Instant, CompactReq<T>, Machine<K, V, T, D>, Sender<Result<(), Error>>)>,
    _phantom: PhantomData<fn() -> D>,
}

A service for performing physical and logical compaction.

This will possibly be called over RPC in the future. Physical compaction is merging adjacent batches. Logical compaction is advancing timestamps to a new since and consolidating the resulting updates.

Fields

cfg: PersistConfig

metrics: Arc<Metrics>

sender: Sender<(Instant, CompactReq<T>, Machine<K, V, T, D>, Sender<Result<(), Error>>)>

_phantom: PhantomData<fn() -> D>

Implementations

impl<K, V, T, D> Compactor<K, V, T, D>

where K: Debug + Codec, V: Debug + Codec, T: Timestamp + Lattice + Codec64 + Sync, D: Semigroup + Ord + Codec64 + Send + Sync,

pub fn new( cfg: PersistConfig, metrics: Arc<Metrics>, write_schemas: Schemas<K, V>, gc: GarbageCollector<K, V, T, D>, ) -> Self

pub fn compact_and_apply_background( &self, req: CompactReq<T>, machine: &Machine<K, V, T, D>, ) -> Option<Receiver<Result<(), Error>>>

Enqueues a CompactReq to be consumed by the compaction background task when available.

Returns a receiver that indicates when compaction has completed. The receiver can be safely dropped at any time if the caller does not wish to wait on completion.

pub(crate) async fn compact_and_apply( machine: &Machine<K, V, T, D>, req: CompactReq<T>, write_schemas: Schemas<K, V>, ) -> Result<RoutineMaintenance, Error>

pub async fn compact_all( stream: impl Stream<Item = Result<FueledMergeRes<T>, Error>>, req: CompactReq<T>, ) -> Result<CompactRes<T>, Error>

pub async fn apply( res: FueledMergeRes<T>, metrics: &Metrics, machine: &Machine<K, V, T, D>, ) -> Result<RoutineMaintenance, Error>

pub fn compact_stream( cfg: CompactConfig, blob: Arc<dyn Blob>, metrics: Arc<Metrics>, shard_metrics: Arc<ShardMetrics>, isolated_runtime: Arc<IsolatedRuntime>, req: CompactReq<T>, write_schemas: Schemas<K, V>, incremental_enabled: bool, ) -> impl Stream<Item = Result<FueledMergeRes<T>, Error>>

Compacts input batches in bounded memory.

The memory bound is broken into pieces: 1. in-progress work 2. fetching parts from runs 3. additional in-flight requests to Blob

1. In-progress work is bounded by 2 * BatchBuilderConfig::blob_target_size. This usage is met at two mutually exclusive moments:

• When reading in a part, we hold the columnar format in memory while writing its contents into a heap.
• When writing a part, we hold a temporary updates buffer while encoding/writing it into a columnar format for Blob.

2. When compacting runs, only 1 part from each one is held in memory at a time. Compaction will determine an appropriate number of runs to compact together given the memory bound and accounting for the reservation in (1). A minimum of 2 * BatchBuilderConfig::blob_target_size of memory is expected, to be able to at least have the capacity to compact two runs together at a time, and more runs will be compacted together if more memory is available.

3. If there is excess memory after accounting for (1) and (2), we increase the number of outstanding parts we can keep in-flight to Blob.

pub async fn compact( cfg: CompactConfig, blob: Arc<dyn Blob>, metrics: Arc<Metrics>, shard_metrics: Arc<ShardMetrics>, isolated_runtime: Arc<IsolatedRuntime>, req: CompactReq<T>, write_schemas: Schemas<K, V>, ) -> Result<CompactRes<T>, Error>

Compacts the input batches together, returning a single compacted batch. Under the hood this just calls Self::compact_stream and Self::compact_all, but it is a convenience method that allows the caller to not have to deal with the streaming API.

fn chunk_runs<'a>( ordered_runs: &'a [(RunLocation, &'a Description<T>, &'a RunMeta, Cow<'a, [RunPart<T>]>)], cfg: &CompactConfig, metrics: &Metrics, run_reserved_memory_bytes: usize, ) -> Vec<(Vec<(&'a RunLocation, &'a Description<T>, &'a RunMeta, &'a [RunPart<T>])>, usize)>

Chunks runs with the following rules:

1. Runs from multiple batches are allowed to be mixed as long as every run in the the batch is present in the chunk.
2. Otherwise runs are split into chunks of runs from a single batch.

async fn flatten_runs<'a>( req: &'a CompactReq<T>, target_order: RunOrder, blob: &'a dyn Blob, metrics: &'a Metrics, ) -> Result<Vec<(RunLocation, &'a Description<T>, &'a RunMeta, Cow<'a, [RunPart<T>]>)>>

Flattens the runs in the input batches into a single ordered list of runs.

pub(crate) async fn compact_runs( cfg: &CompactConfig, shard_id: &ShardId, desc: &Description<T>, runs: Vec<(&Description<T>, &RunMeta, &[RunPart<T>])>, blob: Arc<dyn Blob>, metrics: Arc<Metrics>, shard_metrics: Arc<ShardMetrics>, isolated_runtime: Arc<IsolatedRuntime>, write_schemas: Schemas<K, V>, ) -> Result<HollowBatch<T>, Error>

Compacts runs together. If the input runs are sorted, a single run will be created as output.

Maximum possible memory usage is (# runs + 2) * [crate::PersistConfig::blob_target_size]

fn validate_req(req: &CompactReq<T>) -> Result<(), Error>

Trait Implementations

impl<K, V, T, D> Clone for Compactor<K, V, T, D>

fn clone(&self) -> Self

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<K: Debug, V: Debug, T: Debug, D: Debug> Debug for Compactor<K, V, T, D>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.