Prototype: function BuildExcerpts ( $docs, $index, $words, $opts=array() )
Excerpts (snippets) builder function. Connects to
searchd, asks it
to generate excerpts (snippets) from given documents, and returns the
$docs is a plain array of strings that carry the documents’
$index is an index name string. Different settings (such
as charset, morphology, wordforms) from given index will be used.
$words is a string that contains the keywords to highlight. They
will be processed with respect to index settings. For instance, if
English stemming is enabled in the index,
shoes will be highlighted
even if keyword is
shoe. Keywords can contain wildcards, that work
similarly to star-syntax available in queries.
$opts is a hash which
contains additional optional highlighting parameters:
before_match: A string to insert before a keyword match. A %PASSAGE_ID% macro can be used in this string. The first match of the macro is replaced with an incrementing passage number within a current snippet. Numbering starts at 1 by default but can be overridden with
start_passage_idoption. In a multi-document call, %PASSAGE_ID% would restart at every given document. Default is
after_match: A string to insert after a keyword match. Starting with version 1.10-beta, a %PASSAGE_ID% macro can be used in this string. Default is
chunk_separator: A string to insert between snippet chunks (passages). Default is
limit: Maximum snippet size, in symbols (codepoints). Integer, default is 256.
around: How much words to pick around each matching keywords block. Integer, default is 5.
exact_phrase: Whether to highlight exact query phrase matches only instead of individual keywords. Boolean, default is false.
use_boundaries: Whether to additionally break passages by phrase boundary characters, as configured in index settings with phrase_boundary directive. Boolean, default is false.
weight_order: Whether to sort the extracted passages in order of relevance (decreasing weight), or in order of appearance in the document (increasing position). Boolean, default is false.
query_mode: Whether to handle $words as a query in extended syntax, or as a bag of words (default behavior). For instance, in query mode (
three four) will only highlight and include those occurrences
three fourwhen the two words from each pair are adjacent to each other. In default mode, any single occurrence of
fourwould be highlighted. Boolean, default is false.
force_all_words: Ignores the snippet length limit until it includes all the keywords. Boolean, default is false.
limit_passages: Limits the maximum number of passages that can be included into the snippet. Integer, default is 0 (no limit).
limit_words: Limits the maximum number of words that can be included into the snippet. Note the limit applies to any words, and not just the matched keywords to highlight. For example, if we are highlighting
Maryand a passage
Mary had a little lambis selected, then it contributes 5 words to this limit, not just 1. Integer, default is 0 (no limit).
start_passage_id: Specifies the starting value of %PASSAGE_ID% macro (that gets detected and expanded in
after_matchstrings). Integer, default is 1.
load_files: Whether to handle $docs as data to extract snippets from (default behavior), or to treat it as file names, and load data from specified files on the server side. Up to dist_threads worker threads per request will be created to parallelize the work when this flag is enabled. Boolean, default is false. Building of the snippets could be parallelized between remote agents. Just set the ‘dist_threads’ param in the config to the value greater than 1, and then invoke the snippets generation over the distributed index, which contain only one(!) local agent and several remotes. The snippets_file_prefix option is also in the game and the final filename is calculated by concatenation of the prefix with given name. Otherwords, when snippets_file_prefix is ‘/var/data’ and filename is ‘text.txt’ the sphinx will try to generate the snippets from the file ‘/var/datatext.txt’, which is exactly ‘/var/data’ + ‘text.txt’.
load_files_scattered: It works only with distributed snippets generation with remote agents. The source files for snippets could be distributed among different agents, and the main daemon will merge together all non-erroneous results. So, if one agent of the distributed index has ‘file1.txt’, another has ‘file2.txt’ and you call for the snippets with both these files, the sphinx will merge results from the agents together, so you will get the snippets from both ‘file1.txt’ and ‘file2.txt’. Boolean, default is false.
load_filesis also set, the request will return the error in case if any of the files is not available anywhere. Otherwise (if
load_filesis not set) it will just return the empty strings for all absent files. The master instance reset this flag when distributes the snippets among agents. So, for agents the absence of a file is not critical error, but for the master it might be so. If you want to be sure that all snippets are actually created, set both
load_files. If the absence of some snippets caused by some agents is not critical for you - set just
html_strip_mode: HTML stripping mode setting. Defaults to
index, which means that index settings will be used. The other values are
strip, that forcibly skip or apply stripping irregardless of index settings; and
retain, that retains HTML markup and protects it from highlighting. The
retainmode can only be used when highlighting full documents and thus requires that no snippet size limits are set. String, allowed values are
allow_empty: Allows empty string to be returned as highlighting result when a snippet could not be generated (no keywords match, or no passages fit the limit). By default, the beginning of original text would be returned instead of an empty string. Boolean, default is false.
passage_boundary: Ensures that passages do not cross a sentence, paragraph, or zone boundary (when used with an index that has the respective indexing settings enabled). String, allowed values are
emit_zones: Emits an HTML tag with an enclosing zone name before each passage. Boolean, default is false.
Snippets extraction algorithm currently favors better passages (with
closer phrase matches), and then passages with keywords not yet in
snippet. Generally, it will try to highlight the best match with the
query, and it will also to highlight all the query keywords, as made
possible by the limits. In case the document does not match the query,
beginning of the document trimmed down according to the limits will be
return by default. You can also return an empty snippet instead case by
allow_empty option to true.
Returns false on failure. Returns a plain array of strings with excerpts (snippets) on success.
Prototype: function BuildKeywords ( $query, $index, $hits )
Extracts keywords from query using tokenizer settings for given index, optionally with per-keyword occurrence statistics. Returns an array of hashes with per-keyword information.
$query is a query to extract keywords from.
$index is a name of
the index to get tokenizing settings and keyword occurrence statistics
$hits is a boolean flag that indicates whether keyword
occurrence statistics are required.
$keywords = $cl->BuildKeywords ( "this.is.my query", "test1", false );
Prototype: function EscapeString ( $string )
Escapes characters that are treated as special operators by the query language parser. Returns an escaped string.
$string is a string to escape.
This function might seem redundant because it’s trivial to implement in any calling application. However, as the set of special characters might change over time, it makes sense to have an API call that is guaranteed to escape all such characters at all times.
$escaped = $cl->EscapeString ( "escaping-sample@query/string" );
Prototype: function FlushAttributes ()
searchd to flush pending attribute updates to disk, and
blocks until completion. Returns a non-negative internal
flush tag on
success. Returns -1 and sets an error message on error.
Attribute values updated using
API call are only kept in RAM until a so-called flush (which writes the
current, possibly updated attribute values back to disk).
FlushAttributes() call lets you enforce a flush. The call will block
searchd finishes writing the data to disk, which might take
seconds or even minutes depending on the total data size (.spa file
size). All the currently updated indexes will be flushed.
Flush tag should be treated as an ever growing magic number that does not mean anything. It’s guaranteed to be non-negative. It is guaranteed to grow over time, though not necessarily in a sequential fashion; for instance, two calls that return 10 and then 1000 respectively are a valid situation. If two calls to FlushAttrs() return the same tag, it means that there were no actual attribute updates in between them, and therefore current flushed state remained the same (for all indexes).
$status = $cl->FlushAttributes (); if ( $status<0 ) print "ERROR: " . $cl->GetLastError();
Prototype: function Status ()
Queries searchd status, and returns an array of status variable name and value pairs.
$status = $cl->Status (); foreach ( $status as $row ) print join ( ": ", $row ) . "\n";
Prototype: function UpdateAttributes ( $index, $attrs, $values, $mva=false, $ignorenonexistent=false )
Instantly updates given attribute values in given documents. Returns number of actually updated documents (0 or more) on success, or -1 on failure.
$index is a name of the index (or indexes) to be updated.
is a plain array with string attribute names, listing attributes that
$values is a hash where key is document ID, and value
is a plain array of new attribute values. Optional boolean parameter
mva points that there is update of MVA attributes. In this case the
values must be a dict with int key (document ID) and list of lists of int values (new MVA attribute values). Optional boolean parameter
points that the update will silently ignore any warnings about trying to
update a column which is not exists in current index schema.
$index can be either a single index name or a list, like in
Query(), wildcard is not allowed and all the
indexes to update must be specified explicitly. The list of indexes can
include distributed index names. Updates on distributed indexes will be
pushed to all agents.
The updates only work with
docinfo=extern storage strategy. They are
very fast because they’re working fully in RAM, but they can also be
made persistent: updates are saved on disk on clean
initiated by SIGTERM signal. With additional restrictions, updates are
also possible on MVA attributes; refer to
directive for details.
$cl->UpdateAttributes ( "test1", array("group_id"), array(1=>array(456)) ); $cl->UpdateAttributes ( "products", array ( "price", "amount_in_stock" ), array ( 1001=>array(123,5), 1002=>array(37,11), 1003=>(25,129) ) );
The first sample statement will update document 1 in index
group_id to 456. The second one will update documents 1001,
1002 and 1003 in index
products. For document 1001, the new price will
be set to 123 and the new amount in stock to 5; for document 1002, the
new price will be 37 and the new amount will be 11; etc.