{"id":5848,"date":"2018-10-06T13:32:50","date_gmt":"2018-10-06T20:32:50","guid":{"rendered":"http:\/\/www.couchbase.com\/blog\/?p=5848"},"modified":"2025-06-13T20:19:56","modified_gmt":"2025-06-14T03:19:56","slug":"ycsb-json-implementation-for-couchbase-and-mongodb","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/ycsb-json-implementation-for-couchbase-and-mongodb\/","title":{"rendered":"YCSB-JSON: Implementaci\u00f3n para Couchbase y MongoDB"},"content":{"rendered":"

YCSB es una gran herramienta de benchmarking construida para ser f\u00e1cilmente extendida por cualquier driver que soporte e implemente operaciones b\u00e1sicas como: insertar, leer, actualizar, borrar y escanear.\u00a0<\/span>Los datos sint\u00e9ticos simples introducidos por YCSB se ajustan perfectamente a este paradigma. <\/span><\/p>\n

Pero cuando se trata de trabajar con bases de datos JSON como Couchbase y MongoDB, YCSB es \u00fatil porque las consultas se vuelven mucho m\u00e1s sofisticadas: consulta de matrices y objetos anidados, ejecuci\u00f3n de uniones y agregaciones.<\/span><\/p>\n

Por un lado, la extensi\u00f3n YCSB-JSON deber\u00eda ser capaz de utilizar todas las operaciones JSON posibles soportadas por una base de datos.
\n<\/span>Por otra parte, la aplicaci\u00f3n de este enfoque debe ser lo suficientemente gen\u00e9rico como para ser f\u00e1cilmente extendido de YCSB y MongoDB, Couchbase, o\u00a0cualquier<\/em> otro controlador de base de datos, independientemente del nivel de consulta JSON que admita.<\/span><\/p>\n

La conexi\u00f3n YCSB-JSON est\u00e1 dise\u00f1ada para emular mejor los escenarios realistas del usuario final. Est\u00e1 dise\u00f1ada para funcionar con cualquier dato JSON, ya sean conjuntos de datos reales, pseudorrealistas o totalmente sint\u00e9ticos. Y uno de los requisitos de la herramienta es que no haya valores codificados en los predicados de consulta. Los usuarios s\u00f3lo pueden controlar la cardinalidad de los datos durante el proceso de generaci\u00f3n del conjunto de datos.\u00a0<\/span><\/p>\n

\"\"<\/p>\n

\u00a0Fig. 1. Un vistazo a la implementaci\u00f3n de YCSB-JSON<\/p>\n

Modelo de datos<\/b><\/h4>\n

El modelo de datos que elegimos para esta comparativa est\u00e1 bien descrito en este art\u00edculo: <\/span>https:\/\/dzone.com\/articles\/ycsb-json-benchmarking-json-databases-by-extending<\/span><\/a>
\nEl conjunto de datos se genera utilizando una herramienta fakeit y se carga en una base de datos (Couchbase, MongoDB) mediante scripts externos. <\/span>Mientras que el modelo est\u00e1 definido y los valores fijos se generan aleatoriamente, estos datos se generan aleatoriamente pero no son sint\u00e9ticos.<\/span><\/p>\n

 <\/p>\n

Gesti\u00f3n de datos <\/b><\/h4>\n

Para cada operaci\u00f3n de la carga de trabajo, las consultas son fijas, pero los valores l\u00edmite de cada predicado parametrizado son no deterministas. Por lo tanto, se eligi\u00f3 el siguiente flujo de gesti\u00f3n de datos:
\n<\/span><\/p>\n

    \n
  1. Generar documentos por fakeit.\u00a0<\/span><\/li>\n
  2. Carga los datos generados en una base de datos mediante cualquier script externo.<\/span><\/li>\n
  3. Ejecuta la fase de carga. Durante esta fase el YCSB leer\u00e1 un subconjunto aleatorio de los documentos generados, almacenar\u00e1 todos sus valores en su cach\u00e9 interna.<\/span><\/li>\n
  4. Durante la fase de ejecuci\u00f3n, el YCSB utilizar\u00e1 los valores de su cach\u00e9 mientras vincula y ejecuta consultas contra la base de datos.<\/span><\/li>\n<\/ol>\n

     <\/p>\n

    Generador de predicados<\/b><\/h4>\n

    El YCSB utiliza generadores cuando opera con datos. El conector introduce su propio generador mapeado a un modelo de datos particular. La asignaci\u00f3n y el modelo s\u00f3lo existen dentro del espacio de nombres del generador. La salida del generador es un conjunto de predicados gen\u00e9ricos (pares campo-valor) para consultas concretas. Esto permite a los usuarios modificar los modelos y ampliar la herramienta con otras consultas sin modificar el resto del c\u00f3digo central.<\/span><\/p>\n

    Generador de predicados: Generador.java\u00a0<\/a><\/span><\/h5>\n

     <\/p>\n

    Ejemplo #1:\u00a0 Consulta de paginaci\u00f3n<\/strong><\/span><\/p>\n

    Una de las operaciones YCSB-JSON, la consulta de paginaci\u00f3n, puede representarse mediante la siguiente sentencia:
    \n<\/span><\/p>\n

    SELECT * FROM WHERE address.zip = OFFSET LIMIT<\/span><\/em><\/p>\n

    El predicado de la consulta es un campo dentro de un objeto. Cuando se usa Couchbase N1QL el campo puede ser simplemente accedido como \"direccion.zip\". Pero otras bases de datos pueden no ser tan flexibles por lo que el generador YCSB-JSON crea 2 predicados: el predicado padre (direcci\u00f3n) y el predicado hijo\/anidado (zip).<\/span><\/p>\n

    Y el predicado hijo tiene un valor elegido aleatoriamente de la lista de valores de muestra para este campo en particular.\u00a0<\/span><\/p>\n

    La siguiente funci\u00f3n genera el Objeto SoeQueryPredicate<\/a>
    \n<\/span>D\u00f3nde nombre<\/code> es \"<\/span>direcci\u00f3n<\/span>\"
    \n<\/span>Y predicado anidado<\/code> es otro objeto SoeQueryPredicate con el nombre \"<\/span>zip<\/span>\"y valor <\/span>\u00a0:<\/span><\/p>\n

    \"\"<\/p>\n

     <\/p>\n

    Ejemplo #2 \u00a0Consulta del informe<\/strong><\/span><\/p>\n

    Los predicados para consultas m\u00e1s complejas se generan de la misma manera. La \u00fanica diferencia es que cuando la consulta introduce varios predicados, la secuencia de predicados (matriz de predicados) se genera en lugar de un \u00fanico predicado. A continuaci\u00f3n se muestra la consulta Informe:<\/span><\/p>\n

    SELECT o2.mes, c2.direcci\u00f3n.zip, SUMA(o2.precio_venta) <\/span><\/em>FROM c2
    \nINNER JOIN pedidos o2 ON KEYS c2.lista_pedidos
    \n<\/span>WHERE c2.direcci\u00f3n.zip = \"valor\" AND o2.mes = \"valor\"
    \n<\/span>GROUP BY o2.mes, c2.direcci\u00f3n.zip ORDER BY SUM(o2.precio_venta)<\/span><\/em><\/p>\n

    Funci\u00f3n a continuaci\u00f3n genera secuencia de:
    \n<\/span>Predicado \"mes\", predicado \"direcci\u00f3n\" con predicado anidado \"zip\", predicado \"precio_venta\", etc:<\/span><\/p>\n

    \"\"<\/p>\n

    Aqu\u00ed encontrar\u00e1 otros generadores de consultas:
    \n<\/span>    https:\/\/github.com\/couchbaselabs\/YCSB\/blob\/soe\/core\/src\/main\/java\/com\/yahoo\/ycsb\/generator\/soe\/Generator.java<\/span><\/a><\/p>\n

     <\/p>\n

    Nuevas operaciones<\/b><\/h4>\n

    Es necesario actualizar el c\u00f3digo con nuevas operaciones. <\/span><\/p>\n

    Firmas en clase DB:\u00a0<\/span>
    \n    https:\/\/github.com\/couchbaselabs\/YCSB\/blob\/soe\/core\/src\/main\/java\/com\/yahoo\/ycsb\/DB.java#L140<\/span><\/a>:<\/p>\n

    \"\"<\/p>\n

    Implementaciones en DBWrapper:\u00a0<\/span>
    \n    https:\/\/github.com\/couchbaselabs\/YCSB\/blob\/soe\/core\/src\/main\/java\/com\/yahoo\/ycsb\/DBWrapper.java#L346<\/span><\/a>:<\/p>\n

    \"\"<\/p>\n

    Ampliaci\u00f3n de CoreWorkload con nuevas operaciones: SoeWorkload.java<\/a><\/span><\/p>\n

     <\/p>\n

    Implementaci\u00f3n de operaciones YCSB-JSON para<\/b>\u00a0Couchbase y MongoDB<\/strong><\/h4>\n

    La funci\u00f3n DB driver de una operaci\u00f3n YCSB-JSON toma un par\u00e1metro adicional que es un objeto generador. Es pasado por la clase Workload y tiene una secuencia de predicado particular pre-construida.<\/span><\/p>\n

    Dado que la estructura y las secuencias de los predicados est\u00e1n bien definidas por el generador, un controlador de BD puede acceder directamente a los nombres y valores y construir la consulta utilizando su lenguaje de consulta nativo u otros m\u00e9todos de acceso. A continuaci\u00f3n se muestran ejemplos de implementaci\u00f3n de consultas de P\u00e1gina e Informe.<\/span><\/p>\n

    Consulta de p\u00e1gina,<\/strong>\u00a0generando una sentencia de consulta para Couchbase:<\/span><\/p>\n

    \"\"<\/p>\n

    para MongoDB:<\/span><\/p>\n

    \"\"<\/p>\n

    \f<\/span><\/p>\n

    Consulta del informe<\/strong>Couchbase:<\/span><\/p>\n

    \"\"<\/p>\n

    MongoDB:<\/span><\/p>\n

    \"\"<\/p>\n

    Todas las implementaciones de Couchbase:\u00a0Couchbase2Client.java<\/a><\/span><\/p>\n

    Todas las implementaciones de MongoDB:\u00a0MongoDbClient.java<\/a><\/span><\/p>\n

    <\/h4>\n

    Referencias<\/strong><\/h4>\n

    Art\u00edculo parte 1:
    \n    \u00a0https:\/\/www.couchbase.com\/blog\/ycsb-json-benchmarking-json-databases-by-extending-ycsb\/<\/a><\/p>\n

    Implementaci\u00f3n de YCSB-JSON:
    \n    https:\/\/github.com\/couchbaselabs\/YCSB\/tree\/soe<\/a><\/p>\n

    FakeIt:
    \n    \u00a0https:\/\/github.com\/bentonam\/fakeit<\/a><\/p>\n

    <\/h4>\n

    Pr\u00f3ximos pasos<\/b><\/h4>\n

    Implementar un generador tipo fakeit para simplificar la generaci\u00f3n de datos y predicados de consulta.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    YCSB is a great benchmarking tool built to be easily extended by any driver which supports and implements basic operations like: insert, read, update, delete and scan.\u00a0Plain synthetic data introduced by YCSB fits this paradigm perfectly. But when it comes […]<\/p>","protected":false},"author":23019,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1814,1821,1816,1819,9417,1812,2201],"tags":[2279,1572,1261,1309,1725,2278],"ppma_author":[9074],"class_list":["post-5848","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-application-design","category-couchbase-architecture","category-couchbase-server","category-data-modeling","category-performance","category-n1ql-query","category-tools-sdks","tag-benchmark","tag-database","tag-json","tag-mongodb","tag-nosql-database","tag-ycsb"],"acf":[],"yoast_head":"\nYCSB-JSON: Implementation for Couchbase and MongoDB<\/title>\n<meta name=\"description\" content=\"For JSON databases such as Couchbase and MongoDB, YCSB is helpful for executing more sophisticated queries. Learn how to use YCSB-JSON today.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/es\/ycsb-json-implementation-for-couchbase-and-mongodb\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"YCSB-JSON: Implementation for Couchbase and MongoDB\" \/>\n<meta property=\"og:description\" content=\"For JSON databases such as Couchbase and MongoDB, YCSB is helpful for executing more sophisticated queries. 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