docs: rfc for table compaction

docs/rfcs/2023-02-01-table-compaction.md

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+---
+Feature Name: "table-compaction"
+Tracking Issue: https://github.com/GreptimeTeam/greptimedb/issues/930
+Date: 2023-02-01
+Author: "Lei, HUANG <mrsatangel@gmail.com>"
+---
+
+# Table Compaction
+
+--- 
+
+## Background
+
+GreptimeDB uses an LSM-tree based storage engine that flushes memtables to SSTs for persistence. 
+But currently it only supports level 0. SST files in level 0 does not guarantee to contain only rows with disjoint time ranges. 
+That is to say, different SST files in level 0 may contain overlapped timestamps. 
+The consequence is, in order to retrieve rows in some time range, all files need to be scanned, which brings a lot of IO overhead.
+
+Also, just like other LSMT engines, delete/update to existing primary keys are converted to new rows with delete/update mark and appended to SSTs on flushing. 
+We need to merge the operations to same primary keys so that we don't have to go through all SST files to find the final state of these primary keys.  
+
+## Goal
+
+Implement a compaction framework to: 
+- maintain SSTs in timestamp order to accelerate queries with timestamp condition;
+- merge rows with same primary key;
+- purge expired SSTs;
+- accommodate other tasks like data rollup/indexing.
+
+
+## Overview
+
+Table compaction involves following components:
+- Compaction scheduler: run compaction tasks, limit the consumed resources;
+- Compaction strategy: find the SSTs to compact and determine the output files of compaction.
+- Compaction task: read the rows from input SSTs and write to the output files.
+
+## Implementation
+
+### Compaction scheduler
+
+`CompactionScheduler` is an executor that continuously polls and executes compaction request from a task queue. 
+
+```rust
+#[async_trait]
+pub trait CompactionScheduler {
+    /// Schedules a compaction task.
+    async fn schedule(&self, task: CompactionRequest) -> Result<()>;
+
+    /// Stops compaction scheduler.
+    async fn stop(&self) -> Result<()>;
+}
+```
+
+
+
+### Compaction triggering
+
+Currently, we can check whether to compact tables when memtable is flushed to SST.
+
+https://github.com/GreptimeTeam/greptimedb/blob/4015dd80752e1e6aaa3d7cacc3203cb67ed9be6d/src/storage/src/flush.rs#L245
+
+
+### Compaction strategy
+
+`CompactionStrategy` defines how to pick SSTs in all levels for compaction.   
+
+```rust
+pub trait CompactionStrategy {
+    fn pick(
+        &self,
+        ctx: CompactionContext,
+        levels: &LevelMetas,
+    ) -> Result<CompactionTask>;
+}
+```
+
+The most suitable compaction strategy for time-series scenario would be 
+a hybrid strategy that combines time window compaction with size-tired compaction, just like [Cassandra](https://cassandra.apache.org/doc/latest/cassandra/operating/compaction/twcs.html) and [ScyllaDB](https://docs.scylladb.com/stable/architecture/compaction/compaction-strategies.html#time-window-compaction-strategy-twcs) does.
+
+We can first group SSTs in level n into buckets according to some predefined time window. Within that window, 
+SSTs are compacted in a size-tired manner (find SSTs with similar size and compact them to level n+1). 
+SSTs from different time windows are neven compacted together.
+That strategy guarantees SSTs in each level are mainly sorted in timestamp order which boosts queries with 
+explict timestamp condition, while size-tired compaction minimizes the impact to foreground writes. 
+
+### Alternatives
+
+Currently, GreptimeDB's storage engine [only support two levels](https://github.com/GreptimeTeam/greptimedb/blob/43aefc5d74dfa73b7819cae77b7eb546d8534a41/src/storage/src/sst.rs#L32).
+For level 0, we can start with a simple time-window based leveled compaction, which reads from all SSTs in level 0, 
+align them to time windows with a fixed duration, merge them with SSTs in level 1 within the same time window 
+to ensure there is only one sorted run in level 1.