Consulta 3: \u00a0<\/span><\/p>\nWITH dy\r\nAS (\r\n\tSELECT pl.hnum AS holedn\r\n\t\t,pl.ps.Nat AS country\r\n\t\t,(pl.ps.FN || \" \" || pl.ps.LN) AS name\r\n\t\t,pl.ps.ID AS ID\r\n\t\t,array_length(hps.Sks) AS score\r\n\t\t,hpl.hole AS `hole`\r\n\t\t,hpl.day AS `day`\r\n\tFROM (\r\n\t\tSELECT meta(usopen).id AS hnum\r\n\t\t\t,ps\r\n\t\tFROM usopen USE keys \"holes:1:1\" unnest Ps AS ps\r\n\t\t) pl\r\n\tINNER JOIN (\r\n\t\tSELECT TONUMBER(split(meta(usopen).id, \":\") [1]) AS `hole`\r\n\t\t\t,TONUMBER(split(meta(usopen).id, \":\") [2]) AS `day`\r\n\t\t\t,hps\r\n\t\tFROM usopen unnest Rs AS rs unnest rs.Hs AS hs unnest hs.HPs AS hps\r\n\t\t) hpl ON (pl.ps.ID = hps.ID)\r\n\t)\r\n\t,dx\r\nAS (\r\n\tSELECT d.name\r\n\t\t,sum(CASE \r\n\t\t\t\tWHEN d.day = 1\r\n\t\t\t\t\tTHEN d.score\r\n\t\t\t\tELSE 0\r\n\t\t\t\tEND) R1\r\n\t\t,sum(CASE \r\n\t\t\t\tWHEN d.day = 2\r\n\t\t\t\t\tTHEN d.score\r\n\t\t\t\tELSE 0\r\n\t\t\t\tEND) R2\r\n\t\t,sum(CASE \r\n\t\t\t\tWHEN d.day = 3\r\n\t\t\t\t\tTHEN d.score\r\n\t\t\t\tELSE 0\r\n\t\t\t\tEND) R3\r\n\t\t,sum(CASE \r\n\t\t\t\tWHEN d.day = 4\r\n\t\t\t\t\tTHEN d.score\r\n\t\t\t\tELSE 0\r\n\t\t\t\tEND) R4\r\n\t\t,sum(d.score) T\r\n\tFROM dy AS d\r\n\tGROUP BY d.name\r\n\tORDER BY d.name\r\n\t)\r\nSELECT d2.name\r\n\t,d2.R1\r\n\t,d2.R2\r\n\t,d2.R3\r\n\t,d2.R4\r\n\t,d2.T\r\n\t,RANK() OVER (ORDER BY d2.T + CUT) AS Rank\r\nFROM dx AS d2 \r\nLET CUT = (\r\n\t\tCASE \r\n\t\t\tWHEN (\r\n\t\t\t\t\td2.R1 = 0\r\n\t\t\t\t\tOR d2.R2 = 0\r\n\t\t\t\t\tOR d2.R3 = 0\r\n\t\t\t\t\tOR d2.R4 = 0\r\n\t\t\t\t\t)\r\n\t\t\t\tTHEN 1000\r\n\t\t\tELSE 0\r\n\t\t\tEND\r\n\t\t)\r\nORDER BY Rank<\/pre>\nF\u00edjese en que faltan los puestos 4, 8, 9, 10 y 11 debido a los empates.<\/span><\/p>\nTarea 4: <\/strong>Ahora, vamos a averiguar c\u00f3mo le fue a cada jugador despu\u00e9s de la ronda1, ronda2, ronda3 en comparaci\u00f3n con la ronda final. Utilizando las funciones de ventana, resulta tan f\u00e1cil como hacer desaparecer los malvaviscos cubiertos de chocolate. <\/span><\/h5>\nConsulta 4:<\/strong> Utilice la misma funci\u00f3n RANK(), ordenando por la puntuaci\u00f3n de cada d\u00eda (d\u00eda1, d\u00eda1+d\u00eda2, d\u00eda1+d\u00eda2+d\u00eda3) en lugar de s\u00f3lo por la puntuaci\u00f3n final.\u00a0<\/span><\/p>\nWITH dy AS (\r\n SELECT\r\n pl.hnum AS holedn,\r\n pl.ps.Nat AS country,(pl.ps.FN || \" \" || pl.ps.LN) AS name,\r\n pl.ps.ID AS ID,\r\n array_length(hps.Sks) AS score,\r\n hpl.hole AS `hole`,\r\n hpl.day AS `day`\r\n FROM\r\n (\r\n SELECT\r\n meta(usopen).id AS hnum,\r\n ps\r\n FROM\r\n usopen USE keys \"holes:1:1\" unnest Ps AS ps\r\n ) pl\r\n INNER JOIN (\r\n SELECT\r\n TONUMBER(split(meta(usopen).id, \":\") [1]) AS `hole`,\r\n TONUMBER(split(meta(usopen).id, \":\") [2]) AS `day`,\r\n hps\r\n FROM\r\n usopen unnest Rs AS rs unnest rs.Hs AS hs unnest hs.HPs AS hps\r\n ) hpl ON (pl.ps.ID = hps.ID)\r\n),\r\ndx AS (\r\n SELECT\r\n d.name,\r\n sum(\r\n CASE WHEN d.day = 1 THEN d.score ELSE 0 END\r\n ) R1,\r\n sum(\r\n CASE WHEN d.day = 2 THEN d.score ELSE 0 END\r\n ) R2,\r\n sum(\r\n CASE WHEN d.day = 3 THEN d.score ELSE 0 END\r\n ) R3,\r\n sum(\r\n CASE WHEN d.day = 4 THEN d.score ELSE 0 END\r\n ) R4,\r\n sum(d.score) T\r\n FROM\r\n dy AS d\r\n GROUP BY\r\n d.name\r\n ORDER BY\r\n d.name\r\n)\r\nSELECT\r\n d2.name,\r\n d2.R1,\r\n d2.R2,\r\n d2.R3,\r\n d2.R4,\r\n d2.T,\r\n DENSE_RANK() OVER (\r\n ORDER BY\r\n d2.T + CUT\r\n ) AS rankMoney,\r\n RANK() OVER (\r\n ORDER BY\r\n d2.T + CUT\r\n ) AS rankFinal,\r\n RANK() OVER (\r\n ORDER BY\r\n d2.R1\r\n ) AS round1rank,\r\n RANK() OVER (\r\n ORDER BY\r\n d2.R1 + d2.R2\r\n ) AS round2rank,\r\n RANK() OVER (\r\n ORDER BY\r\n d2.R1 + d2.R2 + d2.R3 + CUT\r\n ) AS round3rank\r\nFROM\r\n dx AS d2 LET CUT = (\r\n CASE WHEN (\r\n d2.R1 = 0\r\n OR d2.R2 = 0\r\n OR d2.R3 = 0\r\n OR d2.R4 = 0\r\n ) THEN 1000 ELSE 0 END\r\n )\r\nORDER BY\r\n rankFinal,\r\n round1rank,\r\n round2rank,\r\n round3rank<\/pre>\n![\"\"](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2018\/12\/Screen-Shot-2018-11-29-at-11.18.45-PM-300x112.png\")
<\/p>\n
Ahora puedes ver c\u00f3mo subieron o bajaron los jugadores cada d\u00eda.<\/span><\/p>\nTarea 5: Crear el cuadro de mando completo para el l\u00edder utilizando las estad\u00edsticas b\u00e1sicas tiro a tiro.<\/strong><\/h5>\nConsulta 5:<\/strong> \u00a0Brooks Koepka es el ganador final del US open. Obtengamos sus puntuaciones, hoyo por hoyo y obtengamos las puntuaciones acumuladas para \u00e9l por ronda. Observa c\u00f3mo la simple SUM() y el agregado COUNT() funcionan como una funci\u00f3n ventana con la cl\u00e1usula OVER().<\/span><\/p>\nSUM(d2.score) OVER (PARTITION BY d2.day ORDER BY d2.hole) hst<\/pre>\nPrimero se divide la puntuaci\u00f3n por d\u00eda y luego por hoyo - especificado por la cl\u00e1usula PARTITION BY, en el orden de los hoyos 1-18. A continuaci\u00f3n, la SUMA suma las puntuaciones hasta el momento.<\/span><\/p>\nSUM(d3.score) OVER (ORDER BY d3.day,d3.hole) ToTScore<\/pre>\nEsta funci\u00f3n SUM() simplemente suma la puntuaci\u00f3n desde el d\u00eda 1, hoyo 1 hasta el d\u00eda 4, hoyo 18 - esto es especificado por el ORDER BY d3.day, d3.hole dentro de la cl\u00e1usula OVER().. El campo ToTScore muestra los cortos totales del torneo por Koepka en cada hoyo.<\/span><\/p>\nWITH dy AS (\r\n SELECT\r\n pl.hnum AS holedn,\r\n pl.ps.Nat AS country,(pl.ps.FN || \" \" || pl.ps.LN) AS name,\r\n pl.ps.ID AS ID,\r\n array_length(hps.Sks) AS score,\r\n hpl.hole AS `hole`,\r\n hpl.day AS `day`,\r\n hpl.Par AS Par\r\n FROM\r\n (\r\n SELECT\r\n meta(usopen).id AS hnum,\r\n ps\r\n FROM\r\n usopen USE keys \"holes:1:1\" unnest Ps AS ps\r\n WHERE\r\n ps.LN = \"Koepka\"\r\n ) pl\r\n INNER JOIN (\r\n SELECT\r\n TONUMBER(split(meta(usopen).id, \":\") [1]) AS `hole`,\r\n TONUMBER(split(meta(usopen).id, \":\") [2]) AS `day`,\r\n hs.Par,\r\n hps\r\n FROM\r\n usopen unnest Rs AS rs unnest rs.Hs AS hs unnest hs.HPs AS hps\r\n ) hpl ON (pl.ps.ID = hps.ID)\r\n),\r\ndx AS (\r\n SELECT\r\n d.name,\r\n d.day,\r\n d.score,\r\n d.hole,\r\n d.Par\r\n FROM\r\n dy AS d\r\n ORDER BY\r\n d.name\r\n),\r\ndz AS (\r\n SELECT\r\n d2.day,\r\n d2.hole,\r\n d2.score,\r\n SUM(d2.score) OVER (\r\n PARTITION BY d2.day\r\n ORDER BY\r\n d2.hole\r\n ) hst,\r\n d2.Par,\r\n SUM(d2.Par) OVER (\r\n PARTITION BY d2.day\r\n ORDER BY\r\n d2.hole\r\n ) hpr\r\n FROM\r\n dx AS d2 LET CUT = (\r\n CASE WHEN (\r\n d2.R1 = 0\r\n OR d2.R2 = 0\r\n OR d2.R3 = 0\r\n OR d2.R4 = 0\r\n ) THEN 1000 ELSE 0 END\r\n )\r\n ORDER BY\r\n d2.day,\r\n d2.hole\r\n)\r\nSELECT\r\n d3.Par,\r\n d3.day,\r\n d3.hole,\r\n d3.hst,\r\n d3.score,(d3.hst - d3.hpr) ToPar,\r\n sum(d3.score) OVER (\r\n ORDER BY\r\n d3.day,\r\n d3.hole\r\n ) ToTScore,\r\n count(1) OVER (\r\n ORDER BY\r\n d3.day,\r\n d3.hole\r\n ) HoleNum\r\nFROM\r\n dz AS d3<\/pre>\n![\"\"](\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/2018\/12\/Screen-Shot-2018-12-02-at-11.54.48-AM-300x207.png\")
<\/p>","protected":false},"excerpt":{"rendered":"
Co-author:\u00a0 Sitaram Vemulapalli, Principal Engineer, Couchbase R&D. \u201cThe answer my friend is hiding in JSON” – Bob Dylan There are a lot of public JSON datasets and then is\u00a0awesome JSON datasets. Every company, including yours, has stored a lot of […]<\/p>","protected":false},"author":55,"featured_media":6074,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1815,2294,1816,1819,1812],"tags":[1261,1725],"ppma_author":[8929],"class_list":["post-6055","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-best-practices-and-tutorials","category-analytics","category-couchbase-server","category-data-modeling","category-n1ql-query","tag-json","tag-nosql-database"],"acf":[],"yoast_head":"\n
JSON to Insights: Fast and Easy - The Couchbase Blog<\/title>\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\/json-to-insights-fast-and-easy\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"JSON to Insights: Fast and Easy\" \/>\n<meta property=\"og:description\" content=\"Co-author:\u00a0 Sitaram Vemulapalli, Principal Engineer, Couchbase R&D. \u201cThe answer my friend is hiding in JSON” – Bob Dylan There are a lot of public JSON datasets and then is\u00a0awesome JSON datasets. 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Previously, he was at MapR, IBM, Informix, Sybase, with more than 20 years of experience in database design & development. He lead the SQL and NoSQL R&D team at IBM Informix. He has received two President's Club awards at Couchbase, two Outstanding Technical Achievement Awards at IBM. 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