Vertica tokenizers

• 1: Preconfigured tokenizers
• 2: Advanced log tokenizer
• 3: Basic log tokenizer
• 4: Whitespace log tokenizer
• 5: ICU tokenizer

1 - Preconfigured tokenizers

The Vertica Analytics Platform provides the following preconfigured tokenizers:

Vertica also provides the following tokenizer, which is not preconfigured:

Examples

The following examples show how you can use a preconfigured tokenizer when creating a text index.

Use the StringTokenizer to create an index from the top_100:

=> CREATE TEXT INDEX idx_100 FROM top_100 on (id, feedback)
                TOKENIZER v_txtindex.StringTokenizer(long varchar)
                 STEMMER v_txtindex.StemmerCaseInsensitive(long varchar);

Use the FlexTokenizer to create an index from unstructured data:

=> CREATE TEXT INDEX idx_unstruc FROM unstruc_data on (__identity__, __raw__)
                                 TOKENIZER public.FlexTokenizer(long varbinary)
                                    STEMMER v_txtindex.StemmerCaseSensitive(long varchar);

Use the StringTokenizerDelim to split a string at the specified delimiter:

=> CREATE TABLE string_table (word VARCHAR(100), delim VARCHAR);
CREATE TABLE
=> COPY string_table FROM STDIN DELIMITER ',';
Enter data to be copied followed by a newline.
End with a backslash and a period on a line by itself.
>>
>> SingleWord,dd
>> Break On Spaces,' '
>> Break:On:Colons,:
>> \.
=> SELECT * FROM string_table;
            word | delim
-----------------+-------
      SingleWord | dd
 Break On Spaces |
 Break:On:Colons | :
(3 rows)

=> SELECT v_txtindex.StringTokenizerDelim(word,delim) OVER () FROM string_table;
      words
-----------------
 Break
 On
 Colons
 SingleWor
 Break
 On
 Spaces
(7 rows)

=> SELECT v_txtindex.StringTokenizerDelim(word,delim) OVER (PARTITION BY word), word as input FROM string_table;
           words | input
-----------------+-----------------
           Break | Break:On:Colons
              On | Break:On:Colons
          Colons | Break:On:Colons
       SingleWor | SingleWord
           Break | Break On Spaces
              On | Break On Spaces
          Spaces | Break On Spaces
(7 rows)

2 - Advanced log tokenizer

Returns tokens that can include minor separators. You can use this tokenizer in situations when your tokens are separated by whitespace or various punctuation. The advanced log tokenizer offers more granularity than the basic log tokenizer in defining separators through the addition of minor separators. This approach is frequently appropriate for analyzing log files.

Parameters

Examples

The following example shows how you can create a text index, from the table foo, using the Advanced Log Tokenizer without a stemmer.

=> CREATE TABLE foo (id INT PRIMARY KEY NOT NULL,text VARCHAR(250));
=> COPY foo FROM STDIN;
End with a backslash and a period on a line by itself.
>> 1|2014-05-10 00:00:05.700433 %ASA-6-302013: Built outbound TCP connection 9986454 for outside:101.123.123.111/443 (101.123.123.111/443)
>> \.
=> CREATE PROJECTION foo_projection AS SELECT * FROM foo ORDER BY id
                                    SEGMENTED BY HASH(id) ALL NODES KSAFE;
=> CREATE TEXT INDEX indexfoo_AdvancedLogTokenizer ON foo (id, text)
                  TOKENIZER v_txtindex.AdvancedLogTokenizer(LONG VARCHAR) STEMMER NONE;
=> SELECT * FROM indexfoo_AdvancedLogTokenizer;
            token            | doc_id
-----------------------------+--------
 %ASA-6-302013:              |      1
 00                          |      1
 00:00:05.700433             |      1
 05                          |      1
 10                          |      1
 101                         |      1
 101.123.123.111/443         |      1
 111                         |      1
 123                         |      1
 2014                        |      1
 2014-05-10                  |      1
 302013                      |      1
 443                         |      1
 700433                      |      1
 9986454                     |      1
 ASA                         |      1
 Built                       |      1
 TCP                         |      1
 connection                  |      1
 for                         |      1
 outbound                    |      1
 outside                     |      1
 outside:101.123.123.111/443 |      1
(23 rows)

3 - Basic log tokenizer

Returns tokens that exclude specified minor separators. You can use this tokenizer in situations when your tokens are separated by whitespace or various punctuation. This approach is frequently appropriate for analyzing log files.

Parameters

Examples

The following example shows how you can create a text index, from the table foo, using the Basic Log Tokenizer without a stemmer.

=> CREATE TABLE foo (id INT PRIMARY KEY NOT NULL,text VARCHAR(250));
=> COPY foo FROM STDIN;
End with a backslash and a period on a line by itself.
>> 1|2014-05-10 00:00:05.700433 %ASA-6-302013: Built outbound TCP connection 9986454 for outside:101.123.123.111/443 (101.123.123.111/443)
>> \.
=> CREATE PROJECTION foo_projection AS SELECT * FROM foo ORDER BY id
                                     SEGMENTED BY HASH(id) ALL NODES KSAFE;
=> CREATE TEXT INDEX indexfoo_BasicLogTokenizer ON foo (id, text)
                 TOKENIZER v_txtindex.BasicLogTokenizer(LONG VARCHAR) STEMMER NONE;
=> SELECT * FROM indexfoo_BasicLogTokenizer;
            token            | doc_id
-----------------------------+--------
 %ASA-6-302013:              |      1
 00:00:05.700433             |      1
 101.123.123.111/443         |      1
 2014-05-10                  |      1
 9986454                     |      1
 Built                       |      1
 TCP                         |      1
 connection                  |      1
 for                         |      1
 outbound                    |      1
 outside:101.123.123.111/443 |      1
(11 rows)

4 - Whitespace log tokenizer

Returns only tokens surrounded by whitespace. You can use this tokenizer in situations where you want to the tokens in your source document to be separated by whitespace characters only. This approach lets you retain the ability to set stop words and token length limits.

Parameters

Examples

The following example shows how you can create a text index, from the table foo, using the Whitespace Log Tokenizer without a stemmer.

=> CREATE TABLE foo (id INT PRIMARY KEY NOT NULL,text VARCHAR(250));
=> COPY foo FROM STDIN;
End with a backslash and a period on a line by itself.
>> 1|2014-05-10 00:00:05.700433 %ASA-6-302013: Built outbound TCP connection 998 6454 for outside:101.123.123.111/443 (101.123.123.111/443)
>> \.
=> CREATE PROJECTION foo_projection AS SELECT * FROM foo ORDER BY id
                                     SEGMENTED BY HASH(id) ALL NODES KSAFE;
=> CREATE TEXT INDEX indexfoo_WhitespaceLogTokenizer ON foo (id, text)
                TOKENIZER v_txtindex.WhitespaceLogTokenizer(LONG VARCHAR) STEMMER NONE;
=> SELECT * FROM indexfoo_WhitespaceLogTokenizer;
            token            | doc_id
-----------------------------+--------
 %ASA-6-302013:              |      1
 (101.123.123.111/443)       |      1
 00:00:05.700433             |      1
 2014-05-10                  |      1
 6454                        |      1
 998                         |      1
 Built                       |      1
 TCP                         |      1
 connection                  |      1
 for                         |      1
 outbound                    |      1
 outside:101.123.123.111/443 |      1
(12 rows)

5 - ICU tokenizer

Supports multiple languages. You can use this tokenizer to identify word boundaries in languages other than English, including Asian languages that are not separated by whitespace.

The ICU Tokenizer is not pre-configured. You configure the tokenizer by first creating a user-defined transform Function (UDTF). Then set the parameter, locale, to identify the language to tokenizer.

Parameters

Example

The following example steps show how you can configure the ICU Tokenizer for simplified Chinese, then create a text index from the table foo, which contains Chinese characters.

For more on how to configure tokenizers, see Configuring a tokenizer.

1. Create the tokenizer using a UDTF. The example tokenizer is named ICUChineseTokenizer.

   VMart=> CREATE OR REPLACE TRANSFORM FUNCTION v_txtindex.ICUChineseTokenizer AS LANGUAGE 'C++' NAME 'ICUTokenizerFactory' LIBRARY v_txtindex.logSearchLib NOT FENCED;
   CREATE TRANSFORM FUNCTION
   

2. Get the procedure ID of the tokenizer.

   VMart=> SELECT proc_oid from vs_procedures where procedure_name = 'ICUChineseTokenizer';
        proc_oid
   -------------------
    45035996280452894
   (1 row)
   

3. Set the parameter, locale, to simplified Chinese. Identify the tokenizer using its procedure ID.

   VMart=> SELECT v_txtindex.SET_TOKENIZER_PARAMETER('locale','zh_CN' using parameters proc_oid='45035996280452894');
    SET_TOKENIZER_PARAMETER
   -------------------------
    t
   (1 row)
   

4. Lock the tokenizer.

   VMart=> SELECT v_txtindex.SET_TOKENIZER_PARAMETER('used','true' using parameters proc_oid='45035996273762696');
    SET_TOKENIZER_PARAMETER
   -------------------------
    t
   (1 row)
   

5. Create an example table, foo, containing simplified Chinese text to index.
   

   VMart=> CREATE TABLE foo(doc_id integer primary key not null,text varchar(250));
   CREATE TABLE
   
   VMart=> INSERT INTO foo values(1, u&'\4E2D\534E\4EBA\6C11\5171\548C\56FD');
    OUTPUT
   --------
         1
   

6. Create an index, index_example, on the table foo. The example creates the index without a stemmer; Vertica stemmers work only on English text. Using a stemmer for English on non-English text can cause incorrect tokenization.
   

   VMart=> CREATE TEXT INDEX index_example ON foo (doc_id, text) TOKENIZER v_txtindex.ICUChineseTokenizer(long varchar) stemmer none;
   CREATE INDEX
   

7. View the new index.
   

   VMart=> SELECT * FROM index_example ORDER BY token,doc_id;
    token  | doc_id
   --------+--------
    中华    |      1
    人民   |      1
    共和国 |      1
   (3 rows)