21 st International Unicode Conference Dublin, Ireland, May 2002 1 Folded Trie: Efficient Data...

121st International Unicode Conference Dublin, Ireland, May 2002

Folded Trie: Efficient Data Structure for All of Unicode

Vladimir Weinstein

[email protected]

Globalization Center of Competency, San Jose, CA


Introduction

• A lot of data for each code point

• Need appropriate data structures

• Unicode version 3.1 introduced code points into supplementary space – addressable range grew to more than a million

• Repetitive data

• Sparsely populated range, especially the supplementary space


Data Structures

• Arrays– Advantages: very fast access time, fast write time

– Disadvantage: Unacceptable memory consumption

• Hash tables– Advantages: Easy to use, Reasonably fast, General

– Disadvantages: High overhead, complicated sequential access, slower than array lookup, data within ranges is not shared


Data Structures (continued)

• Inversion Maps– Advantages: simple, very compact, fast boolean

operations

– Disadvantages: worse access time than arrays and possibly hash tables

• For more details see “Bits of Unicode” at http://www.macchiato.com/slides/Bits_of_Unicode.ppt


Tries

• A trie is a structure with one or more indexes and one data storage.

• Name comes from “Information Retrieval”

• Shares repetitive data

• Good compaction

• Not appropriate for frequently changing data


Single-Index Trie

• A trie structure with an index array and a data array.

• Advantages– Excellent size– Very good access performance (two array accesses,

shift, mask and addition)

• Disadvantages– Not appropriate for frequently changing data– Index array gets too big when dealing with

supplementary code points


Single-Index Trie Diagram

BMP code point Upper Lower

15 0

LOWER_MASK

UPPER_WIDTH LOWER_WIDTH

IndexData Array

0

Data0

Block

Block


Double-Index Trie

• Two index arrays and a data block

• Compared to single-index trie:1. Provides better compression of the index array

2. Worse performance, but still very fast

3. Feasible for supplementary code points


Double-Index Trie Diagram

Block

Code point Upper Middle

20 0

Index 1 Index 2

0

Index2

Lower

Data

0

Data

MIDDLE_MASK LOWER_MASK

UPPER_WIDTH MIDDLE_WIDTH LOWER_WIDTH

Index1


Folded Trie

• Fast access for BMP code points

• Slower access for supplementary code points, but far less frequent

• Compacts supplementary index

• Needs additional build time processing

• Fast address with UTF-16 code units– no need to construct code point


Folded Trie – Supplementary Access Diagram

Lead Surrogate

110110..15 0

0Trail Surrogate

110111..15 9

Pseudo Code Point

Final Data6

Folded Trie

Index + Data

5

1

2

Has data for surrogate block?

No

Yes

3

Data

Same for the surrogate block

44

Lead Surrogate Data

• BMP code points access same as with single-index


ICU Implementation: UTrie

• ICU implementation is called UTrie

• Stores either 16 bit or 32 bit wide data (extensible in the future)

• Up to 256K different data elements

• Can be frozen and reused as memory mapped image for fast startup

• Using UTrie requires custom code

More about ICU at the end of presentation


Range Enumeration

• Allows enumerating over a set of contiguous maximal ranges of same data elements

• Elements can be preprocessed by additional callback

• Saves time when processing the whole Unicode range by efficiently walking the trie structure

start

limit Element 3

Element 2

Element 2

Element 2

Element 2

Element 2

Element 2

Element 1start-1

limit-1


Latin-1 Fast Path

• Build time option

• Allows direct array access for the Latin-1 range (0x00-0xFF)

• Latin-1 range is not compressed if this option is used

• Appropriate when access for Latin-1 range is critical– collation


• Normalization data is stored using UTries

• For example, main data has the following format

Example: Normalization Data

Extra data index Combining class BCK FWD QC_MAYBE

31 15 7 6 5 3

Combines back

Combines forward

Can be either:-index to variable length data- first part of supplementary lookup value-Special handling indicator (Hangul, Jamo)

QC_NO

0

Values for normalization quick check

• Variable-length data contains composition and decomposition info


Example: Character Properties Data

• The result of UTrie lookup is an index

• Double indexing allows for even better compression, since many code points have the same property value

• UTrie data width is 16 bit (thousands of data entries), while the property data width is 32 bits (few hundred unique data words).

Index Data

Folded Trie

16 bits

Property data

32 bits


International Components for Unicode

• International Components for Unicode(ICU) is a library that provides robust and full-featured Unicode support

• Several library services use the common UTrie implementation

• Wide variety of supported platforms • open source (X license – non-viral)• C/C++ and Java versions• http://oss.software.ibm.com/icu/


Conclusion

• UTrie data structure provides good compression with fast access

• The main constraint for usage is the nature of the data that needs to be stored

• Designed for repetitive and sparse data


Q & A


Folding and Surrogate Access

• Folding process compacts the index for supplementaries and moves it right above the BMP index

• Access in ICU4C:– Define a C callback, invoked when special lead

surrogate is detected

– Manually detect special lead surrogates

• In ICU4J, provide a subclass with a method that detects special lead surrogates


Summary

• Introduction: Storing Unicode data

• Types of data structures

• Tries

• Single-index trie

• Double-index trie

• Folded trie

• Usage of folded trie in normalization

• Usage of folded trie for character properties

21 st International Unicode Conference Dublin, Ireland, May 2002 1 Folded Trie: Efficient Data...

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