English Sentence Memory Booster (BSD Book 1)

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It keeps a so-called RAM chunk that stores all the most recent changes. Thus, while most changes on the RT index will be performed in RAM only and complete instantly in milliseconds , those changes that overflow the RAM chunk will stall for the duration of disk chunk creation a few seconds. Since version 2. Disk chunks are, in fact, just regular disk-based indexes. But they're a part of an RT index and automatically managed by it, so you need not configure nor manage them manually. Generally, it is better to set the limit bigger, to minimize both the frequency of flushes, and the index fragmentation number of disk chunks.

A global limit on all indexes is also planned, but not yet implemented yet as of 1. Disk chunk full-text index data can not be actually modified, so the full-text field changes ie. Therefore, on workloads with high full-text updates ratio index might eventually get polluted by these previous row versions, and searching performance would degrade. Physical index purging that would improve the performance is planned, but not yet implemented as of 1. Data in RAM chunk gets saved to disk on clean daemon shutdown, and then loaded back on startup.

However, on daemon or server crash, updates from RAM chunk might be lost. Full-text changes in RT index are transactional. Binary logs are essentially a recovery mechanism.

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With binary logs enabled, searchd writes every given transaction to the binlog file, and uses that for recovery after an unclean shutdown. On clean shutdown, RAM chunks are saved to disk, and then all the binlog files are unlinked. Older, already closed binlog files are kept until all of the transactions stored in them from all indexes are flushed as a disk chunk.

Setting the limit to 0 pretty much prevents binlog from being unlinked at all while searchd is running; however, it will still be unlinked on clean shutdown. This is the default case as of 2. Sync is relatively slow because it has to perform physical disk writes, so mode 1 is the safest every committed transaction is guaranteed to be written on disk but the slowest.

Flushing log to OS prevents from data loss on searchd crashes but not system crashes. Mode 2 is the default. On recovery after an unclean shutdown, binlogs are replayed and all logged transactions since the last good on-disk state are restored. Transactions are checksummed so in case of binlog file corruption garbage data will not be replayed; such a broken transaction will be detected and, currently, will stop replay.

One unwanted side effect of binlogs is that actively updating a small RT index that fully fits into a RAM chunk part will lead to an ever-growing binlog that can never be unlinked until clean shutdown. Binlogs are essentially append-only deltas against the last known good saved state on disk, and unless RAM chunk gets saved, they can not be unlinked. An ever-growing binlog is not very good for disk use and crash recovery time.

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Starting with 2. With periodic flushes enabled, searchd will keep a separate thread, checking whether RT indexes RAM chunks need to be written back to disk. Once that happens, the respective binlogs can be and are safely unlinked. There are no guarantees that the particular RAM chunk will get saved. For instance, it does not make sense to regularly re-save a huge RAM chunk that only gets a few rows worth of updates.

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The search daemon determine whether to actually perform the flush with a few heuristics. So-called matching modes are a legacy feature that used to provide very limited query syntax and ranking support. Currently, they are deprecated in favor of full-text query language and so-called rankers.

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Starting with version 0. All those other modes are actually internally converted to extended syntax anyway. NB, any query terms will be ignored, such that filters, filter-ranges and grouping will still be applied, but no text-matching. In full scan mode, all the indexed documents will be considered as matching. Such queries will still apply filters, sorting, and group by, but will not perform any full-text searching.

This can be useful to unify full-text and non-full-text searching code, or to offload SQL server there are cases when Sphinx scans will perform better than analogous MySQL queries. An example of using the full scan mode might be to find posts in a forum.

By selecting the forum's user ID via SetFilter but not actually providing any search text, Sphinx will match every document i. By default this will be ordered by relevancy, followed by Sphinx document ID in ascending order earliest first. OR operator precedence is higher than AND, so "looking for cat dog mouse" means "looking for cat dog mouse " and not " looking for cat dog mouse". Some transformations performed by this optimization include:.

N BB becomes A B!

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BB if the cost of evaluating N is greater than the added together costs of evaluating A and B. Simplifications are often better for complex queries, or algorithmically generated queries. Queries like "-dog", which implicitly include all documents from the collection, can not be evaluated.

This is both for technical and performance reasons.

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Technically, Sphinx does not always keep a list of all IDs. Performance-wise, when the collection is huge ie. The following special operators and modifiers can be used when using the extended matching mode:. Additionally, the same document must also contain the words 'example' and 'program' in the title field, with up to, but not including, 5 words between the words in question; E.

Additionally, the same document must contain the word 'python' in the body field, but not contain either 'php' or 'perl';. There always is implicit AND operator, so "hello world" means that both "hello" and "world" must be present in matching document. Field limit operator limits subsequent searching to a given field. Normally, query will fail with an error message if given field name does not exist in the searched index. However, that can be suppressed by specifying " relaxed" option at the very beginning of the query:.

Field position limit, introduced in version 0. For example, " body[50] hello" will not match the documents where the keyword 'hello' occurs at position 51 and below in the body. Proximity distance is specified in words, adjusted for word count, and applies to all words within quotes. Quorum matching operator introduces a kind of fuzzy matching. It will only match those documents that pass a given threshold of given words. Operator is limited to keywords.

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Instead of an absolute number, you can also specify a number between 0. Strict order operator aka operator "before" , introduced in version 0. Order operator has the lowest priority. It can be applied both to just keywords and more complex expressions, ie. Exact form keyword modifier, introduced in version 0. The default behavior is to match the document if the stemmed keyword matches. This is a modifier that affects the keyword and thus can be used within operators such as phrase, proximity, and quorum operators.