Execution of fetch queries

With all the SQL drivers, building a plain table generally works as follows.

• connection to the database is established;
• pre query as sql_query_pre is executed to perform any necessary initial setup, such as setting per-connection encoding with MySQL;
• main query as sql_query is executed and the rows it returns are processed;
• post-query as sql_query_post is executed to perform any necessary cleanup;
• connection to the database is closed;
• indexer does the sorting phase (to be pedantic, table-type specific post-processing);
• connection to the database is established again;
• post-processing query as sql_query_post_index is executed to perform any necessary final cleanup;
• connection to the database is closed again.

Example of a source fetching data from MYSQL:

source mysource {
  type             = mysql
  path             = /path/to/realtime
  sql_host         = localhost
  sql_user         = myuser
  sql_pass         = mypass
  sql_db           = mydb
  sql_query_pre    = SET CHARACTER_SET_RESULTS=utf8
  sql_query_pre    = SET NAMES utf8
  sql_query        =  SELECT id, title, description, category_id  FROM mytable
  sql_query_post   = DROP TABLE view_table
  sql_query_post_index = REPLACE INTO counters ( id, val ) \
    VALUES ( 'max_indexed_id', $maxid )
  sql_attr_uint    = category_id
  sql_field_string = title
 }
table mytable {
  type   = plain
  source = mysource
  path   = /path/to/mytable
  ...
 }

sql_query

This is the query which is used to retrieve documents from SQL server. There can be only one sql_query declared and it’s mandatory to have one. See also Processing fetched data

sql_query_pre

Pre-fetch query, or pre-query. Multi-value, optional, default is empty list of queries. They are executed before the sql_query exactly in order of appearance in the configuration file. Pre-query results are ignored.

Pre-queries are useful in a lot of ways. They are used to setup encoding, mark records that are going to be indexed, update internal counters, set various per-connection SQL server options and variables, and so on.

Perhaps the most frequent pre-query usage is to specify the encoding that the server will use for the rows it returns. Note that Manticore accepts only UTF-8 texts. Two MySQL specific examples of setting the encoding are:

sql_query_pre = SET CHARACTER_SET_RESULTS=utf8
sql_query_pre = SET NAMES utf8

Also specific to MySQL sources, it is useful to disable query cache (for indexer connection only) in pre-query, because indexing queries are not going to be re-run frequently anyway, and there’s no sense in caching their results. That could be achieved with:

sql_query_pre = SET SESSION query_cache_type=OFF

sql_query_post

Post-fetch query. Optional, default value is empty.

This query is executed immediately after sql_query completes successfully. When post-fetch query produces errors, they are reported as warnings, but indexing is not terminated. It’s result set is ignored. Note that indexing is not yet completed at the point when this query gets executed, and further indexing still may fail. Therefore, any permanent updates should not be done from here. For instance, updates on helper table that permanently change the last successfully indexed ID should not be run from sql_query_post query; they should be run from sql_query_post_index query instead.

sql_query_post_index

Post-processing query. Optional, default value is empty.

This query is executed when indexing is fully and successfully completed. If this query produces errors, they are reported as warnings, but indexing is not terminated. It’s result set is ignored. $maxid macro can be used in its text; it will be expanded to maximum document ID which was actually fetched from the database during indexing. If no documents were indexed, $maxid will be expanded to 0.

Example:

sql_query_post_index = REPLACE INTO counters ( id, val ) \
    VALUES ( 'max_indexed_id', $maxid )

The difference between sql_query_post and sql_query_post_index is in that sql_query_post is run immediately when Manticore received all the documents, but further indexing may still fail for some other reason. On the contrary, by the time the sql_query_post_index query gets executed, it is guaranteed that the table was created successfully. Database connection is dropped and re-established because sorting phase can be very lengthy and would just timeout otherwise.

Processing fetched data

By default the first column from the result set of sql_query is indexed as the document id.

Document ID MUST be the very first field, and it MUST BE UNIQUE SIGNED (NON-ZERO) INTEGER NUMBER from -9223372036854775808 to 9223372036854775807.

You can specify up to 32 full-text fields (formally, up to SPH_MAX_FIELDS from sphinx.h), and an arbitrary amount of attributes. All of the columns that are neither document ID (the first one) nor attributes will be indexed as full-text fields.

Declaration of attributes:

sql_attr_bigint

Declares a 64-bit signed integer.

sql_attr_bool

Declares a boolean attribute. It’s equivalent to an integer attribute with bit count of 1.

sql_attr_float

Declares a floating point attribute.

The values will be stored in single precision, 32-bit IEEE 754 format. Represented range is approximately from 1e-38 to 1e+38. The amount of decimal digits that can be stored precisely is approximately 7.

One important usage of the float attributes is storing latitude and longitude values (in radians), for further usage in query-time geosphere distance calculations.

sql_attr_json

Declares a JSON attribute.

When indexing JSON attributes, Manticore expects a text field with JSON formatted data. JSON attributes supports arbitrary JSON data with no limitation in nested levels or types.

sql_attr_multi

Declares a multi-value attribute.

Plain attributes only allow to attach 1 value per each document. However, there are cases (such as tags or categories) when it is desired to attach multiple values of the same attribute and be able to apply filtering or grouping to value lists.

The MVA can take the values from a column (like the rest of the data types) - in this case the column in the result set must provide a string with multiple integer values separated by comma - or by running a separate query to get the values.

In case of query the engine runs the query, group by result by ids and will attach the values to their corresponding documents in the table. Values with an id not found in the table are discarded.

The declaration format is as follows (backslashes are for clarity only; everything can be declared in a single line as well):

sql_attr_multi = ATTR-TYPE ATTR-NAME 'from' SOURCE-TYPE \
    [;QUERY] \
    [;RANGED-QUERY]

where

• ATTR-TYPE is uint, bigint or timestamp
• SOURCE-TYPE is field, query, ranged-query, or ranged-main-query
• QUERY is SQL query used to fetch all ( docid, attrvalue ) pairs
• RANGED-QUERY is SQL query used to fetch min and max ID values, similar to sql_query_range (used with ranged-query SOURCE-TYPE) If using ranged-main-query SOURCE-TYPE then omit the RANGED-QUERY and it will automatically use the same query from sql_query_range (useful option in complex inheritance setups to save having to manually duplicate the same query many times)

sql_attr_multi = uint tag from field
sql_attr_multi = uint tag from query; SELECT id, tag FROM tags
sql_attr_multi = bigint tag from ranged-query; \
    SELECT id, tag FROM tags WHERE id>=$start AND id<=$end; \
    SELECT MIN(id), MAX(id) FROM tags

sql_attr_string

Declares a string attribute. There is a fixed size limit of 4GB per value.

sql_attr_timestamp

Declares an UNIX timestamp.

Timestamps can store date and time in the range of Jan 01, 1970 to Jan 19, 2038 with a precision of one second. The expected column value should be a timestamp in UNIX format, ie. 32-bit unsigned integer number of seconds elapsed since midnight, January 01, 1970, GMT. Timestamps are internally stored and handled as integers everywhere. But in addition to working with timestamps as integers, it’s also legal to use them along with different date-based functions, such as time segments sorting mode, or day/week/month/year extraction for GROUP BY.

Note that DATE or DATETIME column types in MySQL can not be directly used as timestamp attributes in Manticore; you need to explicitly convert such columns using UNIX_TIMESTAMP function (if data is in range).

Note timestamps can not represent dates before January 01, 1970, and UNIX_TIMESTAMP() in MySQL will not return anything expected. If you only needs to work with dates, not times, consider TO_DAYS() function in MySQL instead.

sql_attr_uint

Declares an unsigned integer attribute.

You can specify bit count for integer attributes by appending ‘:BITCOUNT’ to attribute name (see example below). Attributes with less than default 32-bit size, or bitfields, perform slower.

sql_attr_uint = group_id
sql_attr_uint = forum_id:9 # 9 bits for forum_id

sql_field_string

Declares a combo string attribute/text field. The values will be indexed as a full-text field, but also stored in a string attribute with the same name. Note, it should be only used when you are sure you want the field to be searchable both in a full-text manner and as an attribute (with the ability to sort and group by it). If you just want to be able to fetch the original value of the field you don’t need to do anything for it unless you implicitly removed the field from the stored fields list via stored_fields.

sql_field_string = name

sql_file_field

Declares a file based field.

This directive makes indexer interpret field contents as a file name, and load and process the referred file. Files larger than max_file_field_buffer in size are skipped. Any errors during the file loading (IO errors, missed limits, etc) will be reported as indexing warnings and will not early terminate the indexing. No content will be indexed for such files.

sql_file_field = field_name

sql_joined_field

Joined/payload field fetch query. Multi-value, optional, default is empty list of queries.

sql_joined_field lets you use two different features: joined fields, and payloads (payload fields). It’s syntax is as follows:

sql_joined_field = FIELD-NAME 'from'  ( 'query' | 'payload-query' | 'ranged-query' | 'ranged-main-query' ); \
        QUERY [ ; RANGE-QUERY ]

where

• FIELD-NAME is a joined/payload field name
• QUERY is an SQL query that must fetch values for further processing
• RANGE-QUERY is an optional SQL query that fetches a range of values to process

Joined fields let you avoid JOIN and/or GROUP_CONCAT statements in the main document fetch query (sql_query). This can be useful when SQL-side JOIN is slow, or needs to be offloaded on Manticore side, or simply to emulate MySQL-specific GROUP_CONCAT functionality in case your database server does not support it.

The query must return exactly 2 columns: document ID, and text to append to a joined field. Document IDs can be duplicate, but they must be in ascending order. All the text rows fetched for a given ID will be concatenated together, and the concatenation result will be indexed as the entire contents of a joined field. Rows will be concatenated in the order returned from the query, and separating whitespace will be inserted between them. For instance, if joined field query returns the following rows:

    ( 1, 'red' )
    ( 1, 'right' )
    ( 1, 'hand' )
    ( 2, 'mysql' )
    ( 2, 'manticore' )

then the indexing results would be equivalent to that of adding a new text field with a value of ‘red right hand’ to document 1 and ‘mysql sphinx’’to document 2, including the keyword positions inside the field in the order they come from the query. If the rows needs to be in a specific order, that needs to be explicitly defined in the query.

Joined fields are only indexed differently. There are no other differences between joined fields and regular text fields.

When a single query is not efficient enough or does not work because of the database driver limitations, ranged queries can be used. It works similar to the ranged queries in the main indexing loop. The range will be queried for and fetched upfront once, then multiple queries with different $start and $end substitutions will be run to fetch the actual data.

When using ranged-main-query query then omit the ranged-query and it will automatically use the same query from :ref:sql_query_range (useful option in complex inheritance setups to save having to manually duplicate the same query many times).

Payloads let you create a special field in which, instead of keyword positions, so-called user payloads are stored. Payloads are custom integer values attached to every keyword. They can then be used in search time to affect the ranking.

The payload query must return exactly 3 columns: document ID; keyword; and integer payload value. Document IDs can be duplicate, but they must be in ascending order. Payloads must be unsigned integers within 24-bit range, ie. from 0 to 16777215. For reference, payloads are currently internally stored as in-field keyword positions, but that is not guaranteed and might change in the future.

Currently, the only method to account for payloads is to use SPH_RANK_PROXIMITY_BM25 ranker. On tables with payload fields, it will automatically switch to a variant that matches keywords in those fields, computes a sum of matched payloads multiplied by field weights, and adds that sum to the final rank.

Example:

sql_joined_field = \
        tagstext from query; \
        SELECT docid, CONCAT('tag',tagid) FROM tags ORDER BY docid ASC
sql_joined_field = tag from ranged-query; \
        SELECT id, tag FROM tags WHERE id>=$start AND id<=$end ORDER BY id ASC; \
        SELECT MIN(id), MAX(id) FROM tags

sql_column_buffers

sql_column_buffers = <colname>=<size>[K|M] [, ...]

Per-column buffer sizes. Optional, default is empty (deduce the sizes automatically). Applies to odbc, mssql source types only.

ODBC and MS SQL drivers sometimes can not return the maximum actual column size to be expected. For instance, NVARCHAR(MAX) columns always report their length as 2147483647 bytes to indexer even though the actually used length is likely considerably less. However, the receiving buffers still need to be allocated upfront, and their sizes have to be determined. When the driver does not report the column length at all, Manticore allocates default 1 KB buffers for each non-char column, and 1 MB buffers for each char column. Driver-reported column length also gets clamped by an upper limit of 8 MB, so in case the driver reports (almost) a 2 GB column length, it will be clamped and a 8 MB buffer will be allocated instead for that column. These hard-coded limits can be overridden using the sql_column_buffers directive, either in order to save memory on actually shorter columns, or overcome the 8 MB limit on actually longer columns. The directive values must be a comma-separated lists of selected column names and sizes:

Example:

sql_query = SELECT id, mytitle, mycontent FROM documents
sql_column_buffers = mytitle=64K, mycontent=10M

Ranged queries

Main query, which needs to fetch all the documents, can impose a read lock on the whole table and stall the concurrent queries (eg. INSERTs to MyISAM table), waste a lot of memory for result set, etc. To avoid this, Manticore supports so-called ranged queries. With ranged queries, Manticore first fetches min and max document IDs from the table, and then substitutes different ID intervals into main query text and runs the modified query to fetch another chunk of documents. Here’s an example.

Ranged query usage example:

sql_query_range = SELECT MIN(id),MAX(id) FROM documents
sql_range_step = 1000
sql_query = SELECT * FROM documents WHERE id>=$start AND id<=$end

If the table contains document IDs from 1 to, say, 2345, then sql_query would be run three times:

1. with $start replaced with 1 and $end replaced with 1000;
2. with $start replaced with 1001 and $end replaced with 2000;
3. with $start replaced with 2001 and $end replaced with 2345.

Obviously, that’s not much of a difference for 2000-row table, but when it comes to indexing 10-million-row table, ranged queries might be of some help.

sql_query_range

Defines the range query. The query specified in this option must fetch min and max document IDs that will be used as range boundaries. It must return exactly two integer fields, min ID first and max ID second; the field names are ignored. When enabled, sql_query will be required to contain $start and $end macros. Note that the intervals specified by $start..$end will not overlap, so you should not remove document IDs that are exactly equal to $start or $end from your query.

sql_range_step

Defined the range query step. Default is 1024.

sql_ranged_throttle

Can be used to throttle ranged query. By default there is no throttling. Values are expected in sql_ranged_throttle.

Throttling can be useful when indexer imposes too much load on the database server. It causes the indexer to sleep for given amount of milliseconds once per each ranged query step. This sleep is unconditional, and is performed before the fetch query.

sql_ranged_throttle = 1000 # sleep for 1 sec before each query step