LSM Range Keys for MVCC Bulk Deletes With Lower Disk I/O
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Solution Overview
Problem
Conventional LSM tree storage systems face inefficiencies in performing bulk operations, particularly bulk delete operations, due to the need for proportional reads and writes, which increase disk input/output and compaction work, and are incompatible with multi-version concurrency control (MVCC) soft deletes, lacking support for ranged operations with user-defined semantics.
Innovation Solution
The introduction of generalized range keys in LSM tree storage systems, which allow for efficient implementation of MVCC range delete operations by associating a timestamp with a delete and maintaining deleted data, using a constant number of writes, and enabling iterators to handle both point and range keys with user-defined semantics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional techniques scan all KV pairs within a range and write an update for each individual key, then bulk delete operations can be performed, but the number of reads and writes grows proportionally with the number of KV pairs, increasing disk I/O and compaction work
Solution Approach 1:
The patent merges multiple individual key delete operations into a single bulk range delete operation. Instead of scanning and writing updates for each individual KV pair, the system performs a single write operation that deletes all keys within a specified range [start-key-string, end-key-string), thereby combining numerous discrete operations into one unified operation that dramatically reduces disk I/O.
Solution Approach 2:
The patent segments the key space into manageable ranges that can be operated on as units. By defining delete operations in terms of key ranges rather than individual keys, the system can process segments of the key space efficiently without needing to handle each key separately, reducing the total number of write operations required.
2Productivity
If conventional techniques scan all KV pairs within a range and write an update for each individual key, then bulk delete operations can be performed, but significant LSM tree compaction work is created
Solution Approach 1:
The patent merges multiple individual key delete operations into a single bulk range delete operation. Instead of scanning and writing updates for each individual KV pair, the system performs a single write operation that deletes all keys within a specified range [start-key-string, end-key-string), thereby combining numerous discrete operations into one unified operation that dramatically reduces compaction work.
3Reliability
If locks are used to prevent insertion of new KV pairs within a range, then data consistency is maintained, but an infinite number of possible keys exist between start-key-string and end-key-string making discretization impossible
Solution Approach 1:
The patent transitions from discrete key-level locking to continuous range-level locking by introducing a new dimension of operation. Instead of attempting to discretize and lock individual keys within a range (which would require infinite granularity), the system operates on the continuous range [start-key-string, end-key-string) as a single unit, acquiring locks at the range level rather than the key level. This dimensional shift from discrete to continuous operation space resolves the impossibility of discretizing infinite key possibilities.
4Reliability
If MVCC soft delete operations mark all KV pairs in a range as deleted at a specific timestamp, then historical timestamps are maintained, but requiring a write operation per soft-deleted key increases disk I/O
Solution Approach 1:
The patent merges multiple individual soft delete operations into a single bulk range soft delete operation. Instead of performing write operations for each individual key to mark it as deleted with a timestamp, the system performs a single write operation that marks all keys within the range [start-key-string, end-key-string) as deleted at the specified timestamp, thereby maintaining MVCC consistency while dramatically reducing disk I/O.
Data Source
AI summary
Methods and systems for implementing ranged operations in a distributed computing system are provided. A write operation is received from a client device, wherein the write operation is configured to associate a range key and range key value with a range of key-value (KV) pairs included in a sorted key space, wherein the range corresponds to a key span of the sorted key space defined by a start boundary key and an end boundary key. A range key and range key value is written for the range based on the write operation, wherein an iterator is configured to read a respective value of a KV pair of the range and/or the range key value based on a position of the iterator within the key span.