# Package org.apache.lucene.monitor

Monitoring framework

See: Description

Interface Summary
CustomQueryHandler: Builds a `QueryTree` for a query that needs custom treatment The default query analyzers will use the QueryVisitor API to extract terms from queries.
MatcherFactory<T extends QueryMatch>: Interface for the creation of new CandidateMatcher objects
MonitorQuerySerializer: Serializes and deserializes MonitorQuery objects into byte streams Use this for persistent query indexes
MonitorUpdateListener: For reporting events on a Monitor's query index
QueryTimeListener: Notified of the time it takes to run individual queries against a set of documents
TermFilteredPresearcher.DocumentQueryBuilder: Constructs a document disjunction from a set of terms
TermWeightor: Calculates the weight of a `Term`

Class Summary
CandidateMatcher<T extends QueryMatch>: Class used to match candidate queries selected by a Presearcher from a Monitor query index.
ConcurrentQueryLoader: Utility class for concurrently loading queries into a Monitor.
ExplainingMatch: A query match containing the score explanation of the match
HighlightsMatch: QueryMatch object that contains the hit positions of a matching Query
HighlightsMatch.Hit: Represents an individual hit
MatchingQueries<T extends QueryMatch>: Class to hold the results of matching a single `Document` against queries held in the Monitor
Monitor: A Monitor contains a set of `Query` objects with associated IDs, and efficiently matches them against sets of `Document` objects.
Monitor.QueryCacheStats: Statistics for the query cache and query index
MonitorConfiguration: Encapsulates various configuration settings for a Monitor's query index
MonitorQuery: Defines a query to be stored in a Monitor
MultiMatchingQueries<T extends QueryMatch>: Class to hold the results of matching a batch of `Document`s against queries held in the Monitor
MultipassTermFilteredPresearcher: A TermFilteredPresearcher that indexes queries multiple times, with terms collected from different routes through a querytree.
ParallelMatcher<T extends QueryMatch>: Matcher class that runs matching queries in parallel.
PartitionMatcher<T extends QueryMatch>: A multi-threaded matcher that collects all possible matches in one pass, and then partitions them amongst a number of worker threads to perform the actual matching.
Presearcher: A Presearcher is used by the Monitor to reduce the number of queries actually run against a Document.
PresearcherMatch<T extends QueryMatch>: Wraps a `QueryMatch` with information about which queries were selected by the presearcher
PresearcherMatches<T extends QueryMatch>: Wraps a `MultiMatchingQueries` with information on which presearcher queries were selected
QueryDecomposer: Split a disjunction query into its consituent parts, so that they can be indexed and run separately in the Monitor.
QueryMatch: Represents a match for a specific query and document
QueryTree: A representation of a node in a query tree Queries are analyzed and converted into an abstract tree, consisting of conjunction and disjunction nodes, and leaf nodes containing terms.
RegexpQueryHandler: A query handler implementation that matches Regexp queries by indexing regex terms by their longest static substring, and generates ngrams from Document tokens to match them.
ScoringMatch: A QueryMatch that reports scores for each match
SlowLog: Reports on slow queries in a given match run
SlowLog.Entry: An individual entry in the slow log
TermFilteredPresearcher: Presearcher implementation that uses terms extracted from queries to index them in the Monitor, and builds a disjunction from terms in a document to match them.

## Package org.apache.lucene.monitor Description

## Monitoring framework

This package contains classes to allow the monitoring of a stream of documents with a set of queries. To use, instantiate a `Monitor` object, register queries with it via `Monitor.register(org.apache.lucene.monitor.MonitorQuery...)`, and then match documents against it either individually via `Monitor.match(org.apache.lucene.document.Document, org.apache.lucene.monitor.MatcherFactory)` or in batches via `Monitor.match(org.apache.lucene.document.Document[], org.apache.lucene.monitor.MatcherFactory)`

### Matcher types

A number of matcher types are included:

- `QueryMatch.SIMPLE_MATCHER` — just returns the set of query ids that a Document has matched
- `ScoringMatch.matchWithSimilarity(org.apache.lucene.search.similarities.Similarity)` — returns the set of matching queries, with the score that each one records against a Document
- `— similar to ScoringMatch, but include the full Explanation`
- `— return the matching queries along with the matching terms for each query`

Matchers can be wrapped in `PartitionMatcher` or `ParallelMatcher` to increase performance in low-concurrency systems.

### Pre-filtering of queries

Monitoring is done efficiently by extracting minimal sets of terms from queries, and using these to build a query index. When a document is passed to `Monitor.match(org.apache.lucene.document.Document, org.apache.lucene.monitor.MatcherFactory)`, it is converted into a small index, and the terms dictionary from that index is then used to build a disjunction query to run against the query index. Queries that match this disjunction are then run against the document. In this way, the Monitor can avoid running queries that have no chance of matching. The process of extracting terms and building document disjunctions is handled by a `Presearcher` In addition, extra per-field filtering can be specified by passing a set of keyword fields to filter on. When queries are registered with the monitor, field-value pairs can be added as optional metadata for each query, and these can then be used to restrict which queries a document is checked against. For example, you can specify a language that each query should apply to, and documents containing a value in their language field would only be checked against queries that have that same value in their language metadata. Note that when matching documents in batches, all documents in the batch must have the same values in their filter fields. Query analysis uses the `QueryVisitor` API to extract terms, which will work for all basic term-based queries shipped with Lucene. The analyzer builds a representation of the query called a `QueryTree`, and then selects a minimal set of terms, one of which must be present in a document for that document to match. Individual terms are weighted using a `TermWeightor`, which allows some selectivity when building the term set. For example, given a conjunction of terms (a boolean query with several MUST clauses, or a phrase, span or interval query), we need only extract one term. The TermWeightor can be configured in a number of ways; by default it will weight longer terms more highly. For query sets that contain many conjunctions, it can be useful to extract and index different minimal term combinations. For example, a phrase query on 'the quick brown fox' could index both 'quick' and 'brown', and avoid being run against documents that contain only one of these terms. The `MultipassTermFilteredPresearcher` allows this sort of indexing, taking a minimum term weight so that very common terms such as 'the' can be avoided. Custom Query implementations that are based on term matching, and that implement `Query.visit(org.apache.lucene.search.QueryVisitor)` will work with no extra configuration; for more complicated custom queries, you can register a `CustomQueryHandler` with the presearcher. Included in this package is a `RegexpQueryHandler`, which gives an example of a different method of indexing automaton-based queries by extracting fixed substrings from a regular expression, and then using ngram filtering to build the document disjunction.

### Persistent query sets

By default, `Monitor` instances are ephemeral, storing their query indexes in memory. To make a persistent monitor, build a `MonitorConfiguration` object and call `MonitorConfiguration.setIndexPath(java.nio.file.Path, org.apache.lucene.monitor.MonitorQuerySerializer)` to tell the Monitor to store its query index on disk. All queries registered with this Monitor will need to have a string representation that is also stored, and can be re-parsed by the associated `MonitorQuerySerializer` when the index is loaded by a new Monitor instance.