async-append-only-log

Async append only log

This module is heavily inspired by flumelog-aligned-offset. It is an attempt to implement the same concept but in a simpler fashion, making it easier to reason about the code. A log is the lowest part of the SSB stack, so it should extremly stable while still maintaining good performance.

A log consists of a number of blocks, that contain a number of records. A record is simply it's length, as a 16-bit unsigned integer, followed by the data bytes. A record must be in one and only one block, which means there probably will be some empty space at the end of a block. Blocks are always written in full.

<block>
  <record
    <length: UInt16LE>
    <data: Bytes>
  </record>*
</block>*

In contrast to flumelog-aligned-offset there is no additional length after the data in a record and no pointer at the end of a block. These were there to be able to iterate over the log in reverse, but I have never seen the need for that.

Writing to the log is always async. Note this is different from flumelog-offset and flumelog-aligned-offset. The since observable will be updated once the data is written. The onDrain callback can be used to know when data has been written if needed. Streaming will only emit values that have been written to storage. This is to ensure that a view will never get ahead of the main log and thus end up in a bad state if the system crashes before data is written. get will return values that have not been written to disk yet.

This module is not compatible with flume without a wrapper around stream as it uses the same terminology as JITDB and ssb-db2 of using offset for the byte position of a record instead of seq.

API

Open the log

const OffsetLog = require('async-append-only-log')

const log = OffsetLog('/path/to/log.file', {
  /**
   * Size of the block, in bytes.
   *
   * DEFAULT: 65536
   */
  blockSize: 1024,

  /**
   * Conversion layer as an object of the shape `{encode, decode}`,
   * where `encode` defines a function (item)=>buffer when writing to disk
   * and `decode` defines a function (buffer)=>item, where `item` is what
   * you will directly interact with using async-append-only-log's APIs.
   * For JSON, use `flumecodec/json`.
   *
   * DEFAULT: `{encode: x => x, decode: x => x}`
   */
  codec: { encode, decode },

  /**
   * Amount of time to wait between writes, in milliseconds.
   *
   * DEFAULT: 250
   */
  writeTimeout: 100,

  /**
   * A function that takes a record's buffer and should return a boolean
   * indicating whether the record is "valid". Implement this to ensure the
   * record is not corrupted. When the log is loaded, all records in the latest
   * block will be checked using this.
   *
   * DEFAULT: (recordBuffer) => true
   */
  validateRecord: (recordBuffer) => {
    // ...
  },
})

Write a single record

log.append(item, (err, offset) => {
  // ...
})

Write several records

log.append([item1, item2, item3], (err, offset3) => {
  // ...
})

Write several records, either all fail or all succeed

log.appendTransaction([item1, item2, item3], (err, offset3) => {
  // ...
})

Wait for all ongoing appends to be flushed to disk

log.onDrain(() => {
  // ...
})

Scan all records as a push-stream

log.stream(opts).pipe(sink)

Where

opts = { live, offsets, values, limit, gte, gt }

• live is a boolean indicating that you're interested only in records added after streaming began. DEFAULT: false
• offsets is a boolean indicating you're interested in knowing the offset for each record streamed to the sink. DEFAULT: true
• values is a boolean indicating you're interested in getting the data buffer for each record streamed to the sink. DEFAULT: true
• limit is a number indicating how many records you want from the stream, after which the stream will close. DEFAULT: 0 which means unlimited
• gte and gt and other opts are specific to ltgt

sink = { paused, write, end }

sink is from push-stream

Read a record

log.get(offset, (err, item) => {
  // ...
})

Delete a record

In practice, this will just overwrite the record with zero bytes.

log.del(offset, (err) => {
  // ...
})

Wait for all ongoing deletes to be flushed to disk

log.onDeletesFlushed(() => {
  // ...
})

Keep track of the most recent record

As an obz observable:

log.since((offset) => {
  // ...
})

Get statistics on deleted records

Among other things, this is useful for knowing how much storage space you could save by running compaction, to eliminate deleted records.

log.stats((err, stats) => {
  console.log(stats)
  // { totalBytes, deletedBytes }
})

Compact the log (remove deleted records)

log.compact((err) => {
  // This callback will be called once, when the compaction is done.
})

Note, this functionality is currently not available when running in a browser.

Track progress of compactions

As an obz observable:

log.compactionProgress((progress) => {
  console.log(progress)
  // {
  //   startOffset,
  //   compactedOffset,
  //   unshiftedOffset,
  //   percent,
  //   done,
  //   sizeDiff,
  //   holesFound,
  // }
})

Where

• startOffset: the starting point for compaction. All offsets smaller than this have been left untouched by the compaction algorithm.
• compactedOffset: all records up until this point have been compacted so far.
• unshiftedOffset: offset for the first record that hasn't yet been "moved" to previous slots. Tracking this allows you to see the algorithm proceeding.
• percent: a number between 0 and 1 to indicate the progress of compaction.
• done: a boolean indicating whether compaction is ongoing (false) or done (true).
• sizeDiff: number of bytes freed after compaction is finished. Only available if done is true.
• holesFound: number of deleted records that were found while compaction was ongoing. Only available if done is true.

Close the log

log.close((err) => {
  // ...
})

Benchmarks

Running bench-flumelog reveals the following numbers. Async flumelog is faster that regular flumelog-offset in all categories. The most important numbers are append (used for onboarding) and stream (used for building indexes). Flumelog-aligned-offset is not included in the benchmarks, as it writes every message synchronously rendering the results invalid.

async-append-only-log:

name, ops/second, mb/second, ops, total-mb, seconds
append, 923964.807, 138.002, 4620748, 690.149, 5.001
stream, 1059075.865, 158.182, 4620748, 690.149, 4.363
stream no cache, 1102803.818, 164.713, 4620748, 690.149, 4.19
stream10, 2540947.641, 379.51, 12714902, 1899.068, 5.004
random, 39715.656, 5.931, 198618, 29.664, 5.001

flumelog offset:

name, ops/second, mb/second, ops, total-mb, seconds
append, 306180.037, 45.74, 3064556, 457.817, 10.009
stream, 294511.348, 43.997, 2945408, 440.017, 10.001
stream no cache, 327724.949, 48.959, 3064556, 457.817, 9.351
stream10, 452973.302, 67.67, 4530186, 676.776, 10.001
random, 28774.712, 4.298, 287891, 43.008, 10.005

To run the benchmarks the small bench-flumelog.patch needs to be applied.

JITDB results for more real world benchmarks are available as jitdb-results.