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Signed-off-by: Alex Chi Z <iskyzh@gmail.com>
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Alex Chi Z
2024-01-23 14:54:16 +08:00
parent 016c6ccadc
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README.md
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@@ -57,8 +57,8 @@ We are working on a new version of the mini-lsm tutorial that is split into 3 we
| 1.7 | Bloom Filter and Key Compression | ✅ | ✅ | ✅ |
| 2.1 | Compaction Implementation | ✅ | ✅ | ✅ |
| 2.2 | Compaction Strategy - Simple | ✅ | ✅ | ✅ |
| 2.3 | Compaction Strategy - Tiered | ✅ | 🚧 | 🚧 |
| 2.4 | Compaction Strategy - Leveled | ✅ | 🚧 | 🚧 |
| 2.3 | Compaction Strategy - Tiered | ✅ | ✅ | 🚧 |
| 2.4 | Compaction Strategy - Leveled | ✅ | ✅ | 🚧 |
| 2.5 | Manifest | ✅ | 🚧 | 🚧 |
| 2.6 | Write-Ahead Log | ✅ | 🚧 | 🚧 |
| 2.7 | Batch Write + Checksum | | | |

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mini-lsm-book/src/week2-03-tiered.md
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@@ -19,6 +19,8 @@ The tiered compaction we talk about in this chapter is the same as RocksDB's uni
## Task 2: Integrate with the Read Path
As tiered compaction does not use the L0 level of the LSM state, you should directly flush your memtables to a new tier instead of as an L0 SST. You can use `self.compaction_controller.flush_to_l0()` to know whether to flush to L0. You may use the first output SST id as the level/tier id for your new sorted run.
## Test Your Understanding
* What are the pros/cons of universal compaction compared with simple leveled/tiered compaction?