Dontopedia

query_cache_size

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

query_cache_size has 23 facts recorded in Dontopedia across 6 references, with 5 live disagreements.

23 facts·11 predicates·6 sources·5 in dispute

Mostly:rdf:type(6), has unit(4), has value(2)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (5)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

hasParameterHas Parameter(2)

hasSettingHas Setting(2)

includesIncludes(1)

Other facts (21)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

21 facts
PredicateValueRef
Rdf:typeConfiguration Parameter[1]
Rdf:typeResource Allocation[2]
Rdf:typeMy Sql Configuration Setting[3]
Rdf:typeMemory Parameter[4]
Rdf:typeMy Sql Configuration Setting[5]
Rdf:typeConfig Parameter[6]
Has UnitMegabytes[1]
Has UnitM[3]
Has UnitMegabyte Unit[5]
Has UnitM[6]
Has Value64M[1]
Has Value64[6]
AffectsQuery Caching[5]
AffectsQuery Performance[6]
Has Purposeenable-query-caching[3]
Has Recommended Value64M[3]
Requires Actionenable-and-configure[3]
Recommended Value64M[5]
Configuration Adviceenable and configure the query cache if appropriate[5]
Configured in SectionMysqld Section[5]
Has ConditionAppropriateness Condition[5]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

hasValuebeam/0268e213-9f18-4cde-a3ca-23f6e442f54f
64M
typebeam/0268e213-9f18-4cde-a3ca-23f6e442f54f
ex:ConfigurationParameter
hasUnitbeam/0268e213-9f18-4cde-a3ca-23f6e442f54f
ex:megabytes
typebeam/b7c3a75f-2454-4270-9e06-beac669c1ce3
ex:ResourceAllocation
labelbeam/b7c3a75f-2454-4270-9e06-beac669c1ce3
query cache resource allocation
typebeam/9ba8d202-48c9-428f-8f4a-96815627d3a0
ex:MySQLConfigurationSetting
hasPurposebeam/9ba8d202-48c9-428f-8f4a-96815627d3a0
enable-query-caching
hasRecommendedValuebeam/9ba8d202-48c9-428f-8f4a-96815627d3a0
64M
hasUnitbeam/9ba8d202-48c9-428f-8f4a-96815627d3a0
M
requiresActionbeam/9ba8d202-48c9-428f-8f4a-96815627d3a0
enable-and-configure
typebeam/b393a650-d6fd-43aa-9270-96f0a07719e8
ex:MemoryParameter
typebeam/80acad74-9ace-47e5-af3f-3272629f2c65
ex:MySQLConfigurationSetting
recommendedValuebeam/80acad74-9ace-47e5-af3f-3272629f2c65
64M
configurationAdvicebeam/80acad74-9ace-47e5-af3f-3272629f2c65
enable and configure the query cache if appropriate
affectsbeam/80acad74-9ace-47e5-af3f-3272629f2c65
ex:query-caching
configuredInSectionbeam/80acad74-9ace-47e5-af3f-3272629f2c65
ex:mysqld-section
hasConditionbeam/80acad74-9ace-47e5-af3f-3272629f2c65
ex:appropriateness-condition
hasUnitbeam/80acad74-9ace-47e5-af3f-3272629f2c65
ex:megabyte-unit
typebeam/cb1056c3-1ada-4dc2-81fc-efd623a7eb64
ex:ConfigParameter
labelbeam/cb1056c3-1ada-4dc2-81fc-efd623a7eb64
query_cache_size
hasValuebeam/cb1056c3-1ada-4dc2-81fc-efd623a7eb64
64
hasUnitbeam/cb1056c3-1ada-4dc2-81fc-efd623a7eb64
M
affectsbeam/cb1056c3-1ada-4dc2-81fc-efd623a7eb64
ex:query-performance

References (6)

6 references
  1. ctx:claims/beam/0268e213-9f18-4cde-a3ca-23f6e442f54f
    • full textbeam-chunk
      text/plain1 KBdoc:beam/0268e213-9f18-4cde-a3ca-23f6e442f54f
      Show excerpt
      2. **Query Cache**: ```ini query_cache_type = 1 query_cache_size = 64M ``` ### Summary By systematically monitoring and analyzing various components of your system, you can identify and mitigate potential bottlenecks causing d
  2. ctx:claims/beam/b7c3a75f-2454-4270-9e06-beac669c1ce3
    • full textbeam-chunk
      text/plain1 KBdoc:beam/b7c3a75f-2454-4270-9e06-beac669c1ce3
      Show excerpt
      PUT /_cluster/settings { "persistent": { "indices.queries.cache.enabled": true, "indices.queries.cache.size": "10%" } } ``` ### Step 3: Use Query Caching in Queries When executing queries, you can explicitly enable caching by
  3. ctx:claims/beam/9ba8d202-48c9-428f-8f4a-96815627d3a0
    • full textbeam-chunk
      text/plain1 KBdoc:beam/9ba8d202-48c9-428f-8f4a-96815627d3a0
      Show excerpt
      CREATE INDEX idx_document_id ON documents(document_id); ``` For a covering index: ```sql CREATE INDEX idx_covering ON documents(document_id, column1, column2, ...); ``` Replace `column1`, `column2`, etc., with the actual columns you need
  4. ctx:claims/beam/b393a650-d6fd-43aa-9270-96f0a07719e8
    • full textbeam-chunk
      text/plain1 KBdoc:beam/b393a650-d6fd-43aa-9270-96f0a07719e8
      Show excerpt
      query_cache_size = 64M max_connections = 500 ``` 4. **Implement In-Memory Caching**: Use Redis for caching: ```python import redis r = redis.Redis(host='localhost', port=6379, db=0) def get_document(document_id): cached_doc = r.get
  5. ctx:claims/beam/80acad74-9ace-47e5-af3f-3272629f2c65
    • full textbeam-chunk
      text/plain1 KBdoc:beam/80acad74-9ace-47e5-af3f-3272629f2c65
      Show excerpt
      Sometimes, rewriting the query can help MySQL use the index more effectively. Here are a few tips: 1. **Avoid Wildcard Selects**: Instead of selecting all columns (`*`), specify only the columns you need. This can reduce the amount of d
  6. ctx:claims/beam/cb1056c3-1ada-4dc2-81fc-efd623a7eb64

See also

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