August 2024
Intermediate to advanced
616 pages
22h 8m
Spanish
Content preview from Diseño de aplicaciones intensivas en datos
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Capítulo 6. Particionamiento
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Está claro que debemos romper con lo secuencial y no limitar a los ordenadores. Debemos enunciar definiciones y prever prioridades y descripciones de los datos. Debemos enunciar relaciones, no procedimientos.
Grace Murray Hopper, La gestión y el ordenador del futuro (1962)
En el Capítulo 5 hablamos de la replicación, es decir, de tener varias copias de los mismos datos en distintos nodos. Para conjuntos de datos muy grandes, o un rendimiento de consulta muy alto, esto no es suficiente: necesitamos dividir los datos en particiones, lo que también se conoce comofragmentación.i
Confusión terminológica
Lo que aquí llamamos partición se denomina shard en MongoDB, Elasticsearch y SolrCloud; se conoce comoregión en HBase, pastilla en Bigtable, vnode en Cassandra y Riak, y vBucket en Couchbase. Sin embargo, partición es el término más establecido, así que nos ceñiremos a él.
Normalmente, las particiones se definen de forma que cada dato (cada registro, fila o documento) pertenezca exactamente a una partición. Hay varias formas de conseguirlo, que tratamos en profundidad en este capítulo. En efecto, cada partición es una pequeña base de datos propia, aunque la base de datos puede admitir operaciones que toquen varias particiones a la ...
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