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5.Index Construction 인공지능연구실. 2 목차 Memory-based inversion Sort-based inversion Exploiting index compression Compressed in-memory inversion Comparison.

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Presentation on theme: "5.Index Construction 인공지능연구실. 2 목차 Memory-based inversion Sort-based inversion Exploiting index compression Compressed in-memory inversion Comparison."— Presentation transcript:

1 5.Index Construction 인공지능연구실

2 2 목차 Memory-based inversion Sort-based inversion Exploiting index compression Compressed in-memory inversion Comparison of inversion methods Constructing signature files and bitmaps Dynamic collections

3 3 The problem is the size of the frequency matrix BibleTREC Terms9,020538,244 Doc31,102742,368 4byte integer(each entry) Matrix4x9,020x31,102bytes= over one gigabytes 4 x 538,244 x 742,368bytes= 1.4 terabytes Figure5.1 static One month127 years

4 4 Memory-based inversion Fig5.2( 문서 ), Fig5.3( 역파일 ) Assumed that the linked lists are sorted Dynamic dictionary data structure Linked list(reference point)

5 5 문제점 ? 메모리 Resource 많이 필요 the best method for small collections (Bible…) Random Data 처리 못함

6 6 Sort-based inversion Fig5.4, Fig5.5  시간과 공간을 비교 QSort. 외부 Mergesort [logR] inital Sorted runs Temporary File Merged runs (fully sorted) K block

7 7 문제점 ? Two copies of temp files 10~100Mbyte 범위에 적절

8 8 Exploiting index compression To reduce the resource(space,time) -temporary file 의 압축 (sort-based) -inverted file 을 main memory 에서 만들고, index 를 disk 에 쓰기전에 decompressing Compressing the temporary files Multiway-merging In-place multiway merging

9 9 Compressing the temporary files Chapters 3 and 4 장에서 설명됨 Compression temporary file of t 요소때문에 약간의 압축 손실 발생 ( 예,unary+delta code,TREC collection) ( 가정 ) unary code t-gap( 다음에오는 triple 과의 t 차이값 ) t-gap=0 → code 0, t-gap=1 → 10, t-gap=2 → 110 (0.6Mbyte 필요 )

10 10 Multiway merging Now, processor-intensive than dick- intensive Reduce time by multiway-merge Use if priority queue such as heap

11 11 In-place multiway merging(1) Heap OUTPUT BLOCK1 RUN 1, BLOCK 2 OUTPUT BLOCK2 RUN 2, BLOCK 3 RUN 3, BLOCK 2 1 2 RUN 1, BLOCK 2 RUN 2, BLOCK 2 RUN 3, BLOCK 1 OUTPUT BLOCK3 Blocks in memory One per run Temporary file, On disk Block table In memory

12 12 In-place multiway merging(2) 알고리즘 - 메모리의 각 run 에서 b byte 의 블록이 heap 으로 이동 - heap 에서 메모리내 output 블록으로 b byte 만큼이동 - output 블록은 temporary file 로 다시 쓰여짐 (block table) Slack 의 사용 - 입력프로세스보다 출력프로세스가 먼저 수행 되는 경향으로 빈블럭이 추가됨 Slack 추가 → permutation →compaction → truncation 처리 Second Edition) permutation → truncation 처리

13 13 Compressed in-memory inversion Large memory inversion(1)  Large main memory  array - list of document numbers d, frequencies f dt  Compared in-memory technique (Section 5.1)  next pointer field 필요 없음.  term t : f t   log N  bits f t   log m t  bits (m t : maximum within-document frequency )  preliminary pass 필요 : N, f t, m t

14 14 Compressed in-memory inversion Large memory inversion(2)  Two-pass Golomb-coded in memory  First Pass - count f t, F t - write f t, F t to a lexicon file  Second Pass - read lexicon file - calculate b t, b t w = 2  log((N-ft)/ft) , B t - build a compressed in-memory inverted file - rebuild in-memory inverted file

15 15 Compressed in-memory inversion Lexicon-based partitioning  Subdivide into small tasks  Lexicon-based, no extra disk  make multiple second pass  each processing one load - ex) three second pass  Lexicon-based, extra disk  Time save, Disk Space 낭비

16 16 Compressed in-memory inversion Text-based partitioning  Inversion and Merge  In-memory inverted file 생성  Merge inverted file on disk  Chunk  Information file - frequency of each term in chunk  Second temp disk file - disk current pointer

17 17 Constructing signature files and bitmaps  Enough Main Memory  signature of k documents  k =  8M / W  - W : signature width (bits) - M : main memory (bytes)  Bitmap  build a compressed inverted file  decompress it and store it with unary code

18 18 Dynamic collections(1)  ‘Insert’ operation  append a new document to an existing collection  ‘Edit’ operation  alter, remove  Expanding the text  Expanding the index

19 19 Dynamic collections Expanding the text  Inserting a new document  the text of the collection must be expanded  compression - cope with hitherto unseen symbol  uncompression - escape flag, stored uncompressed  periodically be completely rebuilt  a new compression model

20 20 Dynamic collections Expanding the Index(1)  ‘stop-press’ file  accumulate update in a stop-press file  rebuild when file too large  drawback  reindex (the data) time   The Inverted file  new-inserted document contains many terms  variable-length recoreds

21 21 Dynamic collections Expanding the Index(2)  Issue  suitable file structure  record extension  record insertion

22 22 Dynamic collections Expanding the Index(2)  Block Structure  Fixed length blocks : b bytes - block address table, records, free space - figure 5.15  Main memory - record address table : record number, block number - free list - current last block of the file

23 23 Dynamic collections Expanding the Index(3)  Access record 1) Record number 2) Block address from the record address table 3) Block read into memory 4) The address of the record within the block 5) Read the record

24 24 Dynamic collections Expanding the Index(4)  Expanding a particular record  sufficient free space 1) Block read 2) record 이동, make space 3) extension 추가 4) block table 수정, write  insufficient free space - smallest record remove, insert extension - extended record remove, insert into new block

25 25 Dynamic collections Expanding the Index(5)  Insert a record  free list check - insert 할 block 결정 - new block 생성  Block read/write (disk operation)  general case : 2  worst case : 4  Reduce the number of disk operation  using ‘update cache’


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