{"id":8342,"date":"2020-03-23T12:07:56","date_gmt":"2020-03-23T19:07:56","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=8342"},"modified":"2024-03-26T09:39:54","modified_gmt":"2024-03-26T16:39:54","slug":"json-case-sensitive-insensitive-search-index-data","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/json-case-sensitive-insensitive-search-index-data\/","title":{"rendered":"JSON distingue entre may\u00fasculas y min\u00fasculas. Usted no tiene que hacerlo."},"content":{"rendered":"

Un RoSe en cualquier otro caso oler\u00eda igual de dulce. William Shakespeare<\/a><\/p><\/blockquote>\n

Debes haber aprendido <\/span>normas de capitalizaci\u00f3n<\/span><\/a> en su escuela de gram\u00e1tica, pero la b\u00fasqueda en el mundo real no es tan sensible a las may\u00fasculas. Charles de Gaulle utiliza min\u00fasculas para la \"de\" intermedia, Tony La Russa utiliza may\u00fasculas para \"La\" - puede haber razones etimol\u00f3gicas para ello, pero es poco probable que su agente de servicio al cliente lo recuerde.\u00a0\u00a0 <\/span>Las bases de datos tienen varias sensibilidades. SQL, por defecto, no distingue entre may\u00fasculas y min\u00fasculas en los identificadores y palabras clave, pero s\u00ed en los datos. <\/span>JSON distingue entre may\u00fasculas y min\u00fasculas tanto en los nombres de campo como en los datos. Lo mismo ocurre con N1QL. JSON puede tener lo siguiente. N1QL select-join-proyectar\u00e1 cada campo y valor como un campo y valor distintos.<\/p>\n

SELECT {\"City\": \"San Francisco\", \"city\": \"san francisco\", \"citY\": \"saN fanciscO\"}\r\n\r\n[\r\n  {\r\n    \"$1\": {\r\n      \"City\": \"San Francisco\",\r\n      \"citY\": \"saN fanciscO\",\r\n      \"city\": \"san francisco\"\r\n    }\r\n  }\r\n]<\/pre>\n
En este art\u00edculo hablaremos de c\u00f3mo hacer frente a distinci\u00f3n entre may\u00fasculas y min\u00fasculas en los datos<\/strong>. Sus referencias de campo siguen siendo distingue entre may\u00fasculas y min\u00fasculas<\/strong>. Si usa el caso incorrecto para el nombre del campo, N1QL asume que este es un campo faltante y asigna el valor FALTANTE a ese campo.<\/p>\n
Consideremos un predicado simple en N1QL para buscar todas las permutaciones de casos.<\/p>\n
WHERE name in [\u201cjoe\u201d, \u201cjoE\u201d, \u201cjOe\u201d, \u201cJoe\u201d, \u201cJoE\u201d, \u201cJOe\u201d, \u201cJOE\u201d]\r\n<\/pre>\n
Esto requiere siete b\u00fasquedas diferentes en el \u00edndice.  \"John\" requiere m\u00e1s b\u00fasquedas en el \u00edndice y \"Fitzerald\" a\u00fan m\u00e1s. <\/span>Existe una forma est\u00e1ndar de hacerlo. Basta con crear un \u00edndice bajando el caso del campo y el literal.<\/span><\/p>\n
WHERE LOWER(name) = \u201cjoe\u201d<\/pre>\n
Esta b\u00fasqueda puede hacerse m\u00e1s r\u00e1pida creando el \u00edndice con la expresi\u00f3n correcta.<\/span><\/p>\n
CREATE INDEX i1 ON customer(LOWER(name));<\/pre>\n
Aseg\u00farese de que su consulta est\u00e1 recogiendo el \u00edndice correcto y empuja el predicado a la exploraci\u00f3n del \u00edndice. Y esa es la idea. Las consultas que tienen predicados empujados a la exploraci\u00f3n del \u00edndice se ejecutan mucho m\u00e1s r\u00e1pido que las consultas que no.  Esto es cierto para los predicados y cierto empuje agregado<\/a> tambi\u00e9n.<\/span><\/p>\n
EXPLAIN SELECT * FROM `customer` WHERE LOWER(name) = \"joe\";\r\n\r\n      {\r\n        \"#operator\": \"IndexScan3\",\r\n        \"index\": \"i1\",\r\n        \"index_id\": \"c117bdf583c2e276\",\r\n        \"index_projection\": {\r\n          \"primary_key\": true\r\n        },\r\n        \"keyspace\": \"customer\",\r\n        \"namespace\": \"default\",\r\n        \"spans\": [\r\n          {\r\n            \"exact\": true,\r\n            \"range\": [\r\n              {\r\n                \"high\": \"\\\"joe\\\"\",\r\n                \"inclusion\": 3,\r\n                \"low\": \"\\\"joe\\\"\"\r\n              }\r\n            ]\r\n          }\r\n        ],<\/pre>\n
Insensibilidad a los casos en un escenario de \u00edndice compuesto.<\/strong><\/h5>\n
WHERE LOWER(name) = \u201cjoe\u201d \r\nAND zip = 94821 \r\nAND salary > 500 \r\nAND join_date <= \u201c2017-01-01\u201d \r\nAND LOWER(county) LIKE \u201csan%\u201d<\/pre>\n
CREATE INDEX i2 ON customer(LOWER(name), \r\n                            zip, \r\n                            LOWER(county), \r\n                            join_date, \r\n                            salary)<\/pre>\n
Insensibilidad a may\u00fasculas y min\u00fasculas en funciones Array.<\/strong><\/h5>\n
Funciones de cadena<\/span><\/a> como SPLIT(), SUFFIXES(), muchas de las <\/span>funciones de matriz<\/span><\/a> y <\/span>funciones del objeto<\/span><\/a> s\u00ed devuelven matrices. Entonces, \u00bfc\u00f3mo utilizarlos sin distinguir entre may\u00fasculas y min\u00fasculas?<\/span><\/p>\n
Seguimos el mismo principio que antes.  Crea primero una expresi\u00f3n para minusvalorar los valores antes de procesarlos mediante estas funciones.\u00a0<\/span><\/p>\n
SELECT SPLIT(\"Good Morning, Joe\") as splitresult;\r\n    \"splitresult\": [\r\n      \"Good\",\r\n      \"Morning,\",\r\n      \"Joe\"\r\n    ]\r\n\r\nSELECT SPLIT(LOWER(\u201cGood Morning, Joe\u201d));\r\n    \"splitresult\": [\r\n      \"good\",\r\n      \"morning,\",\r\n      \"joe\"\r\n    ]\r\n<\/pre>\n
Ahora, lo que realmente quieres es filtrar en base a un valor dentro de la cadena.<\/span><\/p>\n
WHERE\u00a0 LOWER(xyz) LIKE \u201c%good%\u201d;<\/pre>\n
Este es probablemente el peor predicado en SQL - en t\u00e9rminos de rendimiento.<\/span><\/p>\n
SELECT * FROM customer\r\nWHERE\u00a0 x IN SPLIT(LOWER(xyz)) SATISFIES x = \u201cgood\u201d END<\/pre>\n
Ahora, \u00bfqu\u00e9 \u00edndice crear\u00edas para esto?\u00a0 CONSEJO<\/a> es muy \u00fatil.<\/span><\/p>\n
CREATE INDEX adv_DISTINCT_split_lower_xyz ON `customer`\r\n           (DISTINCT ARRAY `x` FOR x in split(lower((`xyz`))) END)<\/pre>\n
Como de costumbre, verifique su explicaci\u00f3n.<\/p>\n
        {\r\n            \"#operator\": \"DistinctScan\",\r\n            \"scan\": {\r\n                \"#operator\": \"IndexScan3\",\r\n                \"index\": \"adv_DISTINCT_split_lower_xyz\",\r\n                \"index_id\": \"552ab6c643616fbc\",\r\n                \"index_projection\": {\r\n                    \"primary_key\": true\r\n                },\r\n                \"keyspace\": \"customer\",\r\n                \"namespace\": \"default\",\r\n                \"spans\": [\r\n                    {\r\n                        \"exact\": true,\r\n                        \"range\": [\r\n                            {\r\n                                \"high\": \"\\\"good\\\"\",\r\n                                \"inclusion\": 3,\r\n                                \"low\": \"\\\"good\\\"\"\r\n                            }\r\n                        ]\r\n                    }\r\n                ],\r\n<\/pre>\n
Si desea utilizar UNNEST y una cl\u00e1usula WHERE sencilla, utilice esta consulta. Verifique siempre su explicaci\u00f3n para asegurarse de que los predicados son empujados a la exploraci\u00f3n del \u00edndice.<\/span><\/p>\n
SELECT * FROM customer\u00a0 \r\n              UNNEST SPLIT(LOWER(xyz)) AS x \r\nWHERE \u00a0 x = \"good\"<\/pre>\n
Uso de fichas\u00a0<\/strong><\/h5>\n
La funci\u00f3n TOKENS() simplifica la obtenci\u00f3n de las min\u00fasculas tomando esa opci\u00f3n como argumento.  V\u00e9ase el art\u00edculo <\/span>M\u00e1s que LIKE: B\u00fasqueda eficiente en JSON con N1QL<\/span><\/a> para m\u00e1s detalles y ejemplos<\/span><\/p>\n
Expresiones complejas.<\/strong><\/h5>\n
SELECT *\u00a0\r\n\r\nFROM customer\r\nWHERE lower(fname) || lower(mname) || lower(lname) = \u201cJoeMSmith\u201d<\/pre>\n
\u00bfC\u00f3mo podemos optimizarlo?  Index Advisor al rescate. Otra vez.<\/span><\/p>\n
CREATE INDEX adv_lower_fname_concat_lower_mname_concat_lower_lname \r\n  ON `customer`(lower((`fname`))||lower((`mname`))||lower((`lname`)))<\/pre>\n
Explicar para confirmar el plan:<\/span><\/p>\n
       {\r\n            \"#operator\": \"IndexScan3\",\r\n            \"index\": \"adv_lower_fname_concat_lower_mname_concat_lower_lname\",\r\n            \"index_id\": \"aaa14cbdf14e9cd8\",\r\n            \"index_projection\": {\r\n                \"primary_key\": true\r\n            },\r\n            \"keyspace\": \"customer\",\r\n            \"namespace\": \"default\",\r\n            \"spans\": [\r\n                {\r\n                    \"exact\": true,\r\n                    \"range\": [\r\n                        {\r\n                            \"high\": \"\\\"JoeMSmith\\\"\",\r\n                            \"inclusion\": 3,\r\n                            \"low\": \"\\\"JoeMSmith\\\"\"\r\n                        }\r\n                    ]\r\n                }\r\n            ],\r\n            \"using\": \"gsi\"\r\n        },\r\n<\/pre>\n
B\u00fasqueda de textos completos<\/strong><\/h4>\n
Como te habr\u00e1s dado cuenta, se trata de un problema de procesamiento y consulta de texto. El FTS puede escanear, almacenar y buscar texto de varias maneras.  La b\u00fasqueda insensible a may\u00fasculas y min\u00fasculas es una de ellas. Veamos el plan para una simple consulta de b\u00fasqueda.<\/p>\n
select * from customer\r\nwhere search (name, \"joe\")\r\n\r\n  \"~children\": [\r\n        {\r\n            \"#operator\": \"PrimaryScan3\",\r\n            \"index\": \"#primary\",\r\n            \"index_projection\": {\r\n                \"primary_key\": true\r\n            },\r\n            \"keyspace\": \"customer\",\r\n            \"namespace\": \"default\",\r\n            \"using\": \"gsi\"\r\n        },\r\n        {\r\n            \"#operator\": \"Fetch\",\r\n            \"keyspace\": \"customer\",\r\n            \"namespace\": \"default\"\r\n        },\r\n        {\r\n            \"#operator\": \"Parallel\",\r\n            \"~child\": {\r\n                \"#operator\": \"Sequence\",\r\n                \"~children\": [\r\n                    {\r\n                        \"#operator\": \"Filter\",\r\n                        \"condition\": \"search((`customer`.`name`), \\\"joe\\\")\"\r\n                    },\r\n                    {\r\n                        \"#operator\": \"InitialProject\",\r\n                        \"result_terms\": [\r\n                            {\r\n                                \"expr\": \"self\",\r\n                                \"star\": true\r\n                         }\r\n                        ]\r\n                    }\r\n                ]\r\n            }\r\n        }\r\n    ]\r\n}\r\n<\/pre>\n
Este NO es el plan que quieres... \u00a1Esto es usar un esc\u00e1ner primario!<\/span><\/p>\n
Despu\u00e9s de crear el \u00edndice de texto en el cliente cubo, las cosas van mucho mejor:<\/span><\/p>\n
select * from customer\r\nwhere search (name, \"joe\")\r\n\r\n{\r\n    \"#operator\": \"Sequence\",\r\n    \"~children\": [\r\n        {\r\n            \"#operator\": \"IndexFtsSearch\",\r\n            \"index\": \"trname\",\r\n            \"index_id\": \"3bdb61e5010e8838\",\r\n            \"keyspace\": \"customer\",\r\n            \"namespace\": \"default\",\r\n            \"search_info\": {\r\n                \"field\": \"\\\"`name`\\\"\",\r\n                \"outname\": \"out\",\r\n                \"query\": \"\\\"joe\\\"\"\r\n            },\r\n            \"using\": \"fts\"\r\n        },\r\n<\/pre>\n
El analizador est\u00e1ndar por defecto baja todos los tokens y por lo tanto encontrar\u00e1 todos los \"joe \"s : JOE, joe, Joe, JOe, etc.   Puede definir un analizador personalizado y proporcionar instrucciones espec\u00edficas para minusvalorar los tokens.  He aqu\u00ed un ejemplo.<\/span><\/p>\n
 \"mapping\": {\r\n   \"analysis\": {\r\n    \"analyzers\": {\r\n     \"mylower\": {\r\n      \"token_filters\": [\r\n       \"to_lower\"\r\n      ],\r\n      \"tokenizer\": \"unicode\",\r\n      \"type\": \"custom\"\r\n     }\r\n    }\r\n   },\r\n<\/pre>\n
As\u00ed es como se a\u00f1ade en la interfaz de usuario.  Ver blog fino 8 formas de personalizar los \u00edndices de b\u00fasqueda de texto completo de Couchbase<\/a> para m\u00e1s detalles sobre las distintas formas de personalizar el \u00edndice FTS.\"\"<\/a><\/p>\n
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 <\/p>","protected":false},"excerpt":{"rendered":"
A RoSe by any other case would smell as sweet. William Shakespeare You must have learned capitalization rules in your grammar school, but the real-world search is not so sensitive to capitalization. Charles de Gaulle uses lower case for the […]<\/p>","protected":false},"author":55,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"ppma_author":[8929],"class_list":["post-8342","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"acf":[],"yoast_head":"\nIs JSON Case Sensitive or Not? | Upper + Lowercase Sensitivity<\/title>\n<meta name=\"description\" content=\"In this post, Couchbase demonstrates why JSON is case sensitive in certain fields and how to work with this sensitivity. 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