{"id":3737,"date":"2017-07-18T12:37:02","date_gmt":"2017-07-18T19:37:02","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=3737"},"modified":"2017-07-18T12:37:02","modified_gmt":"2017-07-18T19:37:02","slug":"querying-date-ranges-within-embedded-json-document-arrays-simple-example-using-n1ql-nodejs-docker","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/querying-date-ranges-within-embedded-json-document-arrays-simple-example-using-n1ql-nodejs-docker\/","title":{"rendered":"Consulta de intervalos de fechas en matrices de documentos JSON incrustados. Un ejemplo sencillo con N1QL, Nodejs y Docker"},"content":{"rendered":"

Consultar e indexar arrays de documentos es una de las caracter\u00edsticas m\u00e1s potentes de Couchbase. Encontrar entradas en un array dentro de un rango de fechas espec\u00edfico es un requerimiento com\u00fan. Considera el siguiente caso de uso.<\/p>\n

Historia de usuario:<\/strong> \"Quiero indexar una matriz de historial de cuentas incrustada dentro de los documentos de mi base de datos para poder realizar una consulta de rango para las entradas de la matriz dentro de un intervalo de fechas espec\u00edfico.\"<\/p>\n

Considere la siguiente estructura json:<\/p>\n

{ \r\n \"name\":\"\", \r\n \"username\":\"\", \r\n \"email\":\"\", \r\n \"address\":{ \r\n \"streetA\":\"\", \r\n \"streetC\":\"\", \r\n \"streetD\":\"\", \r\n \"city\":\"\", \r\n \"state\":\"\", \r\n \"country\":\"\", \r\n \"zipcode\":\"\" \r\n \"geo\": {\r\n \"lat\":\"\", \r\n \"lng\":\"\" \r\n }\r\n },\r\n \"phone\":\"\", \r\n \"website\":\"\", \r\n \"company\": {\r\n \"name\":\"\", \r\n \"catchPhrase\":\"\", \r\n \"bs\":\"\" \r\n },\r\n \"posts\": [\r\n {\r\n \"words\":\"\", \r\n \"sentence\":\"\", \r\n \"sentences\":\"\", \r\n \"paragraph\":\"\" \r\n },...\r\n ],\r\n \"accountHistory\": [\r\n {\r\n \"amount\":\"\", \r\n \"date\":\"\", \r\n \"business\":\"\", \r\n \"name\":\"\", \r\n \"type\":\"\", \r\n \"account\":\"\" \r\n },...\r\n ]\r\n}<\/pre>\n
Tengo un array llamado accountHistory<\/strong>\u00a0que podr\u00eda incluir 0-N n\u00famero de entradas.   Si quiero consultar un determinado intervalo de fechas, puedo hacerlo f\u00e1cilmente definiendo un \u00edndice secundario en el campo fecha<\/strong> campo.<\/p>\n
CREATE INDEX date_range ON\r\n default(DISTINCT ARRAY v.date FOR v IN accountHistory END)<\/pre>\n
He creado una entrada de \u00edndice \u00fanica utilizando\u00a0DISTINTO<\/strong><\/a>\u00a0para cada fecha<\/strong> en cada entrada de accountHistory.   Esto significa que cada documento en el cluster que tiene un array de accountHistory<\/strong> se incluir\u00e1n en mi \u00edndice siempre que la entrada accountHistory tenga un campo llamado \"fecha<\/strong>\".  Es posible que tenga varios tipos de elementos en la matriz accountHistory y s\u00f3lo quiero que se incluyan los elementos que tengan un campo de fecha.  Si no hay ning\u00fan campo de fecha, el indizador no incluir\u00e1 esa entrada en el \u00edndice.  Ahora puedo incluir rangos de fechas en mi predicado de consulta:<\/p>\n
SELECT default.email, v.account, v.type, v.amount, v.name, v.email\r\n FROM default\r\n UNNEST accountHistory v\r\nWHERE v.date BETWEEN '2016-02-01T00:00:00.000Z' AND '2017-06-01T00:00:00.000Z'<\/pre>\n
He utilizado una de mis otras caracter\u00edsticas favoritas de N1QL en la consulta:\u00a0UNNEST<\/strong><\/a>.   Me permite dar forma al JSON e incluir campos de nivel de documento ra\u00edz en mis resultados.   En mi consulta, cada entrada devuelta incluir\u00e1 la informaci\u00f3n del historial de la cuenta que est\u00e9 dentro del intervalo de fechas de mi predicado.  Tambi\u00e9n quiero que se incluya la direcci\u00f3n de correo electr\u00f3nico del documento del que procede, y no quiero tener que escribir l\u00f3gica de an\u00e1lisis JSON adicional para desgranarla en mi aplicaci\u00f3n.   Ese es el poder de usar unnest.  La consulta devuelve lo siguiente:<\/p>\n
\"results\": [\r\n {\r\n \"account\": \"68475391\",\r\n \"amount\": \"416.37\",\r\n \"date\": \"2016-02-01T00:00:00.000Z\",\r\n \"email\": \"Emmanuel.Labadie72@gmail.com\",\r\n \"name\": \"Credit Card Account 0008\",\r\n \"type\": \"invoice\"\r\n },...<\/pre>\n
Pru\u00e9balo:<\/strong>\u00a0Docker es mi forma favorita de crear un entorno de desarrollo.   Un repositorio f\u00e1cil de usar para los ejemplos anteriores est\u00e1 en github: n1ql-query-nodejs <\/a>.  Utiliza docker-compose para construir dos servicios:<\/p>\n
    \n
  1. Un servicio de cl\u00faster Couchbase de nodo \u00fanico.<\/li>\n
  2. Un servicio nodejs para aprovisionar el cl\u00faster Couchbase con 250.000 perfiles de usuario e \u00edndices para varios ejemplos, incluyendo consultas de rango de fechas para matrices de documentos.<\/li>\n<\/ol>","protected":false},"excerpt":{"rendered":"
    Querying and indexing document arrays is one of the most powerful features of Couchbase. \u00a0Finding array entries within a specific date range is a common requirement. \u00a0Consider the following use case. User Story: “I want to index an embedded account […]<\/p>","protected":false},"author":20,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1822,1812],"tags":[2012,1519],"ppma_author":[9019],"class_list":["post-3737","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-node-js","category-n1ql-query","tag-array-indexing","tag-docker"],"acf":[],"yoast_head":"\nQuerying Date Ranges within Embedded JSON Document Arrays. 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