ice

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README

ice

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The file is written in the reverse order that we typically access data. This helps us write in one pass since later sections of the file require file offsets of things we've already written.

Current usage:

  • crc-32 bytes and version are in fixed position at the end of the file
  • reading remainder of footer could be version specific
  • remainder of footer gives us:
    • 3 important offsets (docValue, fields index and stored data index)
    • 2 important values (number of docs and chunk factor)
  • field data is processed once and memoized onto the heap so that we never have to go back to disk for it
  • access to stored data by doc number means first navigating to the stored data index, then accessing a fixed position offset into that slice, which gives us the actual address of the data. the first bytes of that section tell us the size of data so that we know where it ends.
  • access to all other indexed data follows the following pattern:
    • first know the field name -> convert to id
    • next navigate to term dictionary for that field
      • some operations stop here and do dictionary ops
    • next use dictionary to navigate to posting list for a specific term
    • walk posting list
    • if necessary, walk posting details as we go
    • if location info is desired, consult location bitmap to see if it is there

stored fields section

  • for each document
    • preparation phase:
      • produce a slice of metadata bytes and data bytes
      • produce these slices in field id order
      • field value is appended to the data slice
      • metadata slice is varint encoded with the following values for each field value
        • field id (uint16)
        • field value start offset in uncompressed data slice (uint64)
        • field value length (uint64)
        • compress the data slice using snappy
    • file writing phase:
      • remember the start offset for this document
      • write out meta data length (varint uint64)
      • write out compressed data length (varint uint64)
      • write out the metadata bytes
      • write out the compressed data bytes

stored fields idx

  • for each document
    • write start offset (remembered from previous section) of stored data (big endian uint64)

With this index and a known document number, we have direct access to all the stored field data.

posting details (freq/norm) section

  • for each posting list
    • produce a slice containing multiple consecutive chunks (each chunk is varint stream)
    • produce a slice remembering offsets of where each chunk starts
    • preparation phase:
      • for each hit in the posting list
      • if this hit is in next chunk close out encoding of last chunk and record offset start of next
      • encode term frequency (uint64)
      • encode norm factor (float32) - similarity specific implementation
    • file writing phase:
      • remember start position for this posting list details
      • write out number of chunks that follow (varint uint64)
      • write out length of each chunk (each a varint uint64)
      • write out the byte slice containing all the chunk data

If you know the doc number you're interested in, this format lets you jump to the correct chunk (docNum/chunkFactor) directly and then seek within that chunk until you find it.

posting details (location) section

  • for each posting list
    • produce a slice containing multiple consecutive chunks (each chunk is varint stream)
    • produce a slice remembering offsets of where each chunk starts
    • preparation phase:
      • for each hit in the posting list
      • if this hit is in next chunk close out encoding of last chunk and record offset start of next
      • encode field (uint16)
      • encode field pos (uint64)
      • encode field start (uint64)
      • encode field end (uint64)
    • file writing phase:
      • remember start position for this posting list details
      • write out number of chunks that follow (varint uint64)
      • write out length of each chunk (each a varint uint64)
      • write out the byte slice containing all the chunk data

If you know the doc number you're interested in, this format lets you jump to the correct chunk (docNum/chunkFactor) directly and then seek within that chunk until you find it.

postings list section

  • for each posting list
    • preparation phase:
      • encode roaring bitmap posting list to bytes (so we know the length)
    • file writing phase:
      • remember the start position for this posting list
      • write freq/norm details offset (remembered from previous, as varint uint64)
      • write location details offset (remembered from previous, as varint uint64)
      • write length of encoded roaring bitmap
      • write the serialized roaring bitmap data

dictionary

  • for each field
    • preparation phase:
      • encode vellum FST with dictionary data pointing to file offset of posting list (remembered from previous)
    • file writing phase:
      • remember the start position of this persistDictionary
      • write length of vellum data (varint uint64)
      • write out vellum data

fields section

  • for each field
    • file writing phase:
      • remember start offset for each field
      • write dictionary address (remembered from previous) (varint uint64)
      • write length of field name (varint uint64)
      • write field name bytes

fields idx

  • for each field
    • file writing phase:
      • write big endian uint64 of start offset for each field

NOTE: currently we don't know or record the length of this fields index. Instead we rely on the fact that we know it immediately precedes a footer of known size.

fields DocValue

  • for each field
    • preparation phase:
      • produce a slice containing multiple consecutive chunks, where each chunk is composed of a meta section followed by compressed columnar field data
      • produce a slice remembering the length of each chunk
    • file writing phase:
      • remember the start position of this first field DocValue offset in the footer
      • write out number of chunks that follow (varint uint64)
      • write out length of each chunk (each a varint uint64)
      • write out the byte slice containing all the chunk data

NOTE: currently the meta header inside each chunk gives clue to the location offsets and size of the data pertaining to a given docID and any read operation leverage that meta information to extract the document specific data from the file.

  • file writing phase
    • write number of docs (big endian uint64)
    • write stored field index location (big endian uint64)
    • write field index location (big endian uint64)
    • write field docValue location (big endian uint64)
    • write out chunk factor (big endian uint32)
    • write out version (big endian uint32)
    • write out file CRC of everything preceding this (big endian uint32)

ice file format diagrams

Legend

Sections
|========|
|        | section
|========|
Fixed-size fields
|--------|        |----|        |--|        |-|
|        | uint64 |    | uint32 |  | uint16 | | uint8
|--------|        |----|        |--|        |-|
Varints
|~~~~~~~~|
|        | varint(up to uint64)
|~~~~~~~~|
Arbitrary-length fields
|--------...---|
|              | arbitrary-length field (string, vellum, roaring bitmap)
|--------...---|
Chunked data
[--------]
[        ]
[--------]

Overview

Footer section describes the configuration of particular ice file. The format of footer is version-dependent, so it is necessary to check V field before the parsing.

        |==================================================|
        | Stored Fields                                    |
        |==================================================|
|-----> | Stored Fields Index                              |
|       |==================================================|   
|       | Dictionaries + Postings + DocValues              | 
|       |==================================================|
| |---> | DocValues Index                                  |
| |     |==================================================|   
| |     | Fields                                           |
| |     |==================================================|
| | |-> | Fields Index                                     |
| | |   |========|========|========|========|====|====|====|
| | |   |     D# |     SF |      F |    FDV | CF |  V | CC | (Footer)
| | |   |========|====|===|====|===|====|===|====|====|====|
| | |                 |        |        |
|-+-+-----------------|        |        |
  | |--------------------------|        |
  |-------------------------------------|

 D#. Number of Docs.
 SF. Stored Fields Index Offset.
  F. Field Index Offset.
FDV. Field DocValue Offset.
 CF. Chunk Factor.
  V. Version.
 CC. CRC32.

Stored Fields

Stored Fields Index is D# consecutive 64-bit unsigned integers - offsets, where relevant Stored Fields Data records are located.

0                                [SF]                   [SF + D# * 8]
| Stored Fields                  | Stored Fields Index              |
|================================|==================================|
|                                |                                  |
|       |--------------------|   ||--------|--------|. . .|--------||
|   |-> | Stored Fields Data |   ||      0 |      1 |     | D# - 1 ||
|   |   |--------------------|   ||--------|----|---|. . .|--------||
|   |                            |              |                   |
|===|============================|==============|===================|
    |                                           |
    |-------------------------------------------|

Stored Fields Data is an arbitrary size record, which consists of metadata and Snappy-compressed data.

Stored Fields Data
|~~~~~~~~|~~~~~~~~|~~~~~~~~...~~~~~~~~|~~~~~~~~...~~~~~~~~|
|    MDS |    CDS |                MD |                CD |
|~~~~~~~~|~~~~~~~~|~~~~~~~~...~~~~~~~~|~~~~~~~~...~~~~~~~~|

MDS. Metadata size.
CDS. Compressed data size.
MD. Metadata.
CD. Snappy-compressed data.

Fields

Fields Index section located between addresses F and len(file) - len(footer) and consist of uint64 values (F1, F2, ...) which are offsets to records in Fields section. We have F# = (len(file) - len(footer) - F) / sizeof(uint64) fields.

(...)                                              [F]                       [F + F#]
| Fields                                           | Fields Index.                  |
|==================================================|================================|
|                                                  |                                |
|   |~~~~~~~~|~~~~~~~~|---...---|~~~~~~~~|~~~~~~~~|||--------|--------|...|--------||
||->|   Dict | Length |    Name | # Docs |Tot Freq|||      0 |      1 |   | F# - 1 ||
||  |~~~~~~~~|~~~~~~~~|---...---|~~~~~~~~|~~~~~~~~|||--------|----|---|...|--------||
||                                                 |              |                 |
||=================================================|==============|=================|
 |                                                                |
 |----------------------------------------------------------------|

Dictionaries + Postings

Each of fields has its own dictionary, encoded in Vellum format. Dictionary consists of pairs (term, offset), where offset indicates the position of postings (list of documents) for this particular term.

|================================================================|- Dictionaries + 
|                                                                |   Postings +
|                                                                |    DocValues
|    Freq/Norm (chunked)                                         |
|    [~~~~~~|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]                      |
| |->[ Freq | Norm (float32 under varint) ]                      |
| |  [~~~~~~|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~]                      |
| |                                                              |
| |------------------------------------------------------------| |
|    Location Details (chunked)                                | |
|    [~~~~~~|~~~~~|~~~~~~~|~~~~~]                              | |
| |->[ Size | Pos | Start | End ]                              | |
| |  [~~~~~~|~~~~~|~~~~~~~|~~~~~]                              | |
| |                                                            | |
| |----------------------|                                     | |
|          Postings List |                                     | |
|         |~~~~~~~~|~~~~~|~~|~~~~~~~~|-----------...--|        | |
|      |->|    F/N |     LD | Length | ROARING BITMAP |        | |
|      |  |~~~~~|~~|~~~~~~~~|~~~~~~~~|-----------...--|        | |
|      |        |----------------------------------------------| |
|      |--------------------------------------|                  |
|          Dictionary                         |                  |
|         |~~~~~~~~|--------------------------|-...-|            |
|      |->| Length | VELLUM DATA : (TERM -> OFFSET) |            |
|      |  |~~~~~~~~|----------------------------...-|            |
|      |                                                         |
|======|=========================================================|- DocValues Index
|      |                                                         |
|======|=========================================================|- Fields
|      |                                                         |
| |~~~~|~~~|~~~~~~~~|---...---|                                  |
| |   Dict | Length |    Name |                                  |
| |~~~~~~~~|~~~~~~~~|---...---|                                  |
|                                                                |
|================================================================|

DocValues

DocValues Index is F# pairs of varints, one pair per field. Each pair of varints indicates start and end point of DocValues slice.

|================================================================|
|     |------...--|                                              |
|  |->| DocValues |<-|                                           |
|  |  |------...--|  |                                           |
|==|=================|===========================================|- DocValues Index
||~|~~~~~~~~~|~~~~~~~|~~|           |~~~~~~~~~~~~~~|~~~~~~~~~~~~||
|| DV1 START | DV1 STOP | . . . . . | DV(F#) START | DV(F#) END ||
||~~~~~~~~~~~|~~~~~~~~~~|           |~~~~~~~~~~~~~~|~~~~~~~~~~~~||
|================================================================|

DocValues is chunked Snappy-compressed values for each document and field.

[~~~~~~~~~~~~~~~|~~~~~~|~~~~~~~~~|-...-|~~~~~~|~~~~~~~~~|--------------------...-]
[ Doc# in Chunk | Doc1 | Offset1 | ... | DocN | OffsetN | SNAPPY COMPRESSED DATA ]
[~~~~~~~~~~~~~~~|~~~~~~|~~~~~~~~~|-...-|~~~~~~|~~~~~~~~~|--------------------...-]

Last 16 bytes are description of chunks.

|~~~~~~~~~~~~...~|----------------|----------------|
|   Chunk Sizes  | Chunk Size Arr |         Chunk# |
|~~~~~~~~~~~~...~|----------------|----------------|

Documentation

Index

Constants

View Source 
const Type string = "ice"
View Source 
const Version uint32 = 3

Variables

This section is empty.

Functions

func Load 

func Load(data *segment.Data) (segment.Segment, error)

Open returns an impl of a segment

func Merge 

func Merge(segments []segment.Segment, drops []*roaring.Bitmap, mergeBufferSize int) segment.Merger

func New 

func New(results []segment.Document, normCalc func(string, int) float32) (
	segment.Segment, uint64, error)

New creates an in-memory implementation of a segment for the source documents

Types

type CollectionStats 

type CollectionStats struct {
	// contains filtered or unexported fields
}

func (*CollectionStats) DocumentCount 

func (c *CollectionStats) DocumentCount() uint64

func (*CollectionStats) Merge 

func (c *CollectionStats) Merge(other segment.CollectionStats)

func (*CollectionStats) SumTotalTermFrequency 

func (c *CollectionStats) SumTotalTermFrequency() uint64

func (*CollectionStats) TotalDocumentCount 

func (c *CollectionStats) TotalDocumentCount() uint64

type DictEntry 

type DictEntry struct {
	// contains filtered or unexported fields
}

func (*DictEntry) Count 

func (d *DictEntry) Count() uint64

func (*DictEntry) Term 

func (d *DictEntry) Term() string

type Dictionary 

type Dictionary struct {
	// contains filtered or unexported fields
}

Dictionary is the representation of the term dictionary

func (*Dictionary) Close 

func (d *Dictionary) Close() error

func (*Dictionary) Contains 

func (d *Dictionary) Contains(key []byte) (bool, error)

func (*Dictionary) Iterator 

func (d *Dictionary) Iterator(a segment.Automaton,
	startKeyInclusive, endKeyExclusive []byte) segment.DictionaryIterator

Iterator returns an iterator which only visits terms having the the vellum automaton and start/end key range

func (*Dictionary) PostingsList 

func (d *Dictionary) PostingsList(term []byte, except *roaring.Bitmap,
	prealloc segment.PostingsList) (segment.PostingsList, error)

PostingsList returns the postings list for the specified term

type DictionaryIterator 

type DictionaryIterator struct {
	// contains filtered or unexported fields
}

DictionaryIterator is an iterator for term dictionary

func (*DictionaryIterator) Close 

func (i *DictionaryIterator) Close() error

func (*DictionaryIterator) Next 

func (i *DictionaryIterator) Next() (segment.DictionaryEntry, error)

Next returns the next entry in the dictionary

type DocumentValueReader 

type DocumentValueReader struct {
	// contains filtered or unexported fields
}

func (*DocumentValueReader) VisitDocumentValues 

func (d *DocumentValueReader) VisitDocumentValues(number uint64, visitor segment.DocumentValueVisitor) error

type Location 

type Location struct {
	// contains filtered or unexported fields
}

Location represents the location of a single occurrence

func (*Location) End 

func (l *Location) End() int

End returns the end byte offset of this occurrence

func (*Location) Field 

func (l *Location) Field() string

Field returns the name of the field (useful in composite fields to know which original field the value came from)

func (*Location) Pos 

func (l *Location) Pos() int

Pos returns the 1-based phrase position of this occurrence

func (*Location) Size 

func (l *Location) Size() int

func (*Location) Start 

func (l *Location) Start() int

Start returns the start byte offset of this occurrence

type Merger 

type Merger struct {
	// contains filtered or unexported fields
}

func (*Merger) DocumentNumbers 

func (m *Merger) DocumentNumbers() [][]uint64

func (*Merger) WriteTo 

func (m *Merger) WriteTo(w io.Writer, closeCh chan struct{}) (n int64, err error)

type Posting 

type Posting struct {
	// contains filtered or unexported fields
}

Posting is a single entry in a postings list

func (*Posting) Frequency 

func (p *Posting) Frequency() int

Frequency returns the frequencies of occurrence of this term in this doc/field

func (*Posting) Locations 

func (p *Posting) Locations() []segment.Location

Locations returns the location information for each occurrence

func (*Posting) Norm 

func (p *Posting) Norm() float64

Norm returns the normalization factor for this posting

func (*Posting) Number 

func (p *Posting) Number() uint64

Number returns the document number of this posting in this segment

func (*Posting) SetNumber 

func (p *Posting) SetNumber(n uint64)

SetNumber sets the document number of this posting

func (*Posting) Size 

func (p *Posting) Size() int

type PostingsIterator 

type PostingsIterator struct {
	Actual   roaring.IntPeekable
	ActualBM *roaring.Bitmap
	// contains filtered or unexported fields
}

PostingsIterator provides a way to iterate through the postings list

func (*PostingsIterator) ActualBitmap 

func (i *PostingsIterator) ActualBitmap() *roaring.Bitmap

ActualBitmap returns the underlying actual bitmap which can be used up the stack for optimizations

func (*PostingsIterator) Advance 

func (i *PostingsIterator) Advance(docNum uint64) (segment.Posting, error)

Advance returns the posting at the specified docNum or it is not present the next posting, or if the end is reached, nil

func (*PostingsIterator) Close 

func (i *PostingsIterator) Close() error

func (*PostingsIterator) Count 

func (i *PostingsIterator) Count() uint64

func (*PostingsIterator) DocNum1Hit 

func (i *PostingsIterator) DocNum1Hit() (uint64, bool)

DocNum1Hit returns the docNum and true if this is "1-hit" optimized and the docNum is available.

func (*PostingsIterator) Empty 

func (i *PostingsIterator) Empty() bool

func (*PostingsIterator) Next 

func (i *PostingsIterator) Next() (segment.Posting, error)

Next returns the next posting on the postings list, or nil at the end

func (*PostingsIterator) ReplaceActual 

func (i *PostingsIterator) ReplaceActual(abm *roaring.Bitmap)

ReplaceActual replaces the ActualBM with the provided bitmap

func (*PostingsIterator) Size 

func (i *PostingsIterator) Size() int

type PostingsList 

type PostingsList struct {
	// contains filtered or unexported fields
}

PostingsList is an in-memory representation of a postings list

func (*PostingsList) Count 

func (p *PostingsList) Count() uint64

Count returns the number of items on this postings list

func (*PostingsList) Iterator 

func (p *PostingsList) Iterator(includeFreq, includeNorm, includeLocs bool,
	prealloc segment.PostingsIterator) (segment.PostingsIterator, error)

Iterator returns an iterator for this postings list

func (*PostingsList) OrInto 

func (p *PostingsList) OrInto(receiver *roaring.Bitmap)

func (*PostingsList) Size 

func (p *PostingsList) Size() int

type Segment 

type Segment struct {
	// contains filtered or unexported fields
}

func (*Segment) CRC 

func (s *Segment) CRC() uint32

CRC returns the CRC value stored in the file footer

func (*Segment) ChunkMode 

func (s *Segment) ChunkMode() uint32

ChunkFactor returns the chunk factor in the file footer

func (*Segment) CollectionStats 

func (s *Segment) CollectionStats(field string) (segment.CollectionStats, error)

func (*Segment) Count 

func (s *Segment) Count() uint64

Count returns the number of documents in this segment.

func (*Segment) Dictionary 

func (s *Segment) Dictionary(field string) (segment.Dictionary, error)

DictionaryReader returns the term dictionary for the specified field

func (*Segment) DocTimeMax 

func (s *Segment) DocTimeMax() uint64

DocTimeMax returns the maximum timestamp of documents in the file footer

func (*Segment) DocTimeMin 

func (s *Segment) DocTimeMin() uint64

DocTimeMin returns the minimum timestamp of documents in the file footer

func (*Segment) DocValueOffset 

func (s *Segment) DocValueOffset() uint64

DocValueOffset returns the docValue offset in the file footer

func (*Segment) DocsMatchingTerms 

func (s *Segment) DocsMatchingTerms(terms []segment.Term) (*roaring.Bitmap, error)

func (*Segment) DocumentValueReader 

func (s *Segment) DocumentValueReader(fields []string) (segment.DocumentValueReader, error)

func (*Segment) Fields 

func (s *Segment) Fields() []string

Fields returns the field names used in this segment

func (*Segment) FieldsIndexOffset 

func (s *Segment) FieldsIndexOffset() uint64

FieldsIndexOffset returns the fields index offset in the file footer

func (*Segment) NumDocs 

func (s *Segment) NumDocs() uint64

NumDocs returns the number of documents in the file footer

func (*Segment) Size 

func (s *Segment) Size() int

func (*Segment) StoredIndexOffset 

func (s *Segment) StoredIndexOffset() uint64

StoredIndexOffset returns the stored value index offset in the file footer

func (*Segment) Timestamp 

func (s *Segment) Timestamp() (int64, int64)

func (*Segment) Type 

func (s *Segment) Type() string

func (*Segment) Version 

func (s *Segment) Version() uint32

Version returns the file version in the file footer

func (*Segment) VisitStoredFields 

func (s *Segment) VisitStoredFields(num uint64, visitor segment.StoredFieldVisitor) error

VisitStoredFields invokes the DocFieldValueVistor for each stored field for the specified doc number

func (*Segment) WriteTo 

func (s *Segment) WriteTo(w io.Writer, _ chan struct{}) (int64, error)

Source Files

View all Source files

Directories

Path Synopsis
cmd
ice
ice/cmd

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