Archival Storage Snapshot Indexing With Deferred B+ Trees
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Solution Overview
Problem
Conventional file systems and backup/archival systems are not designed for efficient long-term storage and retrieval of large quantities of snapshots, leading to increased retrieval times as the number of snapshots grows due to the need to traverse extensive metadata for recent data access.
Innovation Solution
An indexing technique using a B+ tree with a large branching factor is employed to create an index data structure that translates logical offsets of snapshots to data object addresses, allowing efficient retrieval independent of the number of snapshots, with indexing deferred until all data is written to an immutable archive.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If conventional file systems process data indexing together with storage layout and data storage to support immediate access, then recently stored data can be immediately retrieved, but retrieval time increases as the number of snapshots increases due to traversing greater metadata
Solution Approach 1:
The patent segments the indexing process from the storage process by using log-structured formats. Data is written sequentially to logs without immediate indexing, and indexing is performed separately in the background. This segmentation allows rapid data intake while deferred indexing operations build the metadata structures needed for efficient retrieval, resolving the contradiction between fast writing and fast reading regardless of snapshot quantity.
Solution Approach 2:
The patent performs preliminary actions by pre-computing and storing index metadata in log-structured formats during the data ingestion phase. Instead of indexing on-demand during retrieval, the system prepares index structures in advance as data is written to logs, enabling constant-time retrieval operations later independent of the number of snapshots.
2Quantity of substance
If conventional systems maintain large quantities of snapshots for long-term storage, then archival requirements are met, but retrieval efficiency decreases due to extensive metadata traversal
Solution Approach 1:
The patent replaces the traditional mechanical file system metadata traversal mechanism with a log-structured indexing system. Instead of traversing directory structures and metadata links through multiple snapshots, the system uses sequential log entries with embedded index information that can be directly queried, substituting the mechanical traversal process with a more efficient logging and indexing approach that scales independently of snapshot quantity.
Solution Approach 2:
The patent changes the fundamental parameter of how metadata is organized and accessed. Rather than using traditional file system metadata structures that require traversal, the system transforms metadata into log-structured format with direct indexing capabilities. This parameter change in the data organization structure enables retrieval efficiency to remain constant even as the number of snapshots increases to meet archival requirements.
3Loss of time
If data is immediately indexed for live access support, then on-demand retrieval is fast, but write throughput decreases due to concurrent indexing operations
Solution Approach 1:
The patent performs preliminary indexing actions in the background after data is written to logs, rather than concurrently during the write operation. Data is first written sequentially to log files at high speed, and then indexing operations are performed separately on the logged data. This preliminary action separation eliminates indexing overhead from the critical write path, maximizing write throughput while still achieving fast retrieval through pre-computed indexes.
Solution Approach 2:
The patent segments the data processing workflow into distinct phases: a write phase where data is rapidly appended to logs without indexing overhead, and an indexing phase where metadata structures are built from the logged data. This segmentation of concerns allows the write operation to achieve maximum throughput by avoiding concurrent indexing, while the separate indexing phase ensures retrieval efficiency is maintained.
Data Source
AI summary
An indexing technique provides an index data structure for efficient retrieval of a snapshot from a long-term storage service (LTSS) of an archival storage system. The snapshot is generated from typed data of a logical entity, such as a virtual disk (vdisk). The data of the snapshot is replicated to a frontend data service of the LTSS sequentially and organized as one or more data objects for storage by a backend data service of LTSS in an object store of the archival storage system. Metadata associated with the snapshot (i.e., snapshot metadata) is recorded as a log and persistently stored on storage media local to the frontend data service. The snapshot metadata includes information describing the snapshot data, e.g., a logical offset range of a snapshot of the vdisk and, thus, is used to construct the index data structure. Notably, construction of the index data structure is deferred until after the entirety of the snapshot data has been replicated and received by the frontend data service.


