collect

How to tweak LISTAGG to support more than 4000 character in select query?

由 馋奶兔 提交于 2019-11-28 00:18:51
Oracle Database 11g Enterprise Edition Release 11.2.0.2.0 - 64bit Production. I have a table in the below format. Name Department Johny Dep1 Jacky Dep2 Ramu Dep1 I need an output in the below format. Dep1 - Johny,Ramu Dep2 - Jacky I have tried the 'LISTAGG' function, but there is a hard limit of 4000 characters. Since my db table is huge, this cannot be used in the app. The other option is to use the SELECT CAST(COLLECT(Name) But my framework allows me to execute only select queries and no PL/SQL scripts.Hence i dont find any way to create a type using "CREATE TYPE" command which is required

Static context cannot access non-static in Collectors

由 谁说我不能喝 提交于 2019-11-27 02:11:10
问题 I have group of students. First I want to group them by the marks. Then I want to further group those sets into same name students together. Map<Integer,Map<String,List<String>>> groupping = students.stream() .collect(Collectors.groupingBy(Student::getMarks, Collectors.mapping(Student::getName,Collectors.toList()))); I am getting a error saying, Non-static method cannot be refered from a static context. Yes. I am pretty much aware that I cannot refer a non-static method without having an

ruby using the “&:methodname” shortcut from array.map(&:methodname) for hash key strings rather than methodname

由 。_饼干妹妹 提交于 2019-11-27 02:05:46
问题 Most ruby developers know how to save a few keystrokes by doing something like this: array.map(&:methodname) rather than array.map {|x| x.methodname } Is there any way I could apply a similar &:methodname shortcut for calling "methods" (values called via keys) on an array of hashes? In my case its with JSON api results being returned in batches of 60 as arrays of hashes originating from JSON. I tried to do this but was not successful: array.map(&:"keyname") but was not successful, throwing a

what's different between each and collect method in Ruby [duplicate]

由 送分小仙女□ 提交于 2019-11-26 18:35:29
This question already has an answer here: Array#each vs. Array#map 6 answers From this code I don't know the difference between the two methods, collect and each . a = ["L","Z","J"].collect{|x| puts x.succ} #=> M AA K print a.class #=> Array b = ["L","Z","J"].each{|x| puts x.succ} #=> M AA K print b.class #=> Array Array#each takes an array and applies the given block over all items. It doesn't affect the array or creates a new object. It is just a way of looping over items. Also it returns self. arr=[1,2,3,4] arr.each {|x| puts x*2} Prints 2,4,6,8 and returns [1,2,3,4] no matter what Array

pyspark collect_set or collect_list with groupby

由 ☆樱花仙子☆ 提交于 2019-11-26 16:11:05
How can I use collect_set or collect_list on a dataframe after groupby . for example: df.groupby('key').collect_set('values') . I get an error: AttributeError: 'GroupedData' object has no attribute 'collect_set' ksindi You need to use agg. Example: from pyspark import SparkContext from pyspark.sql import HiveContext from pyspark.sql import functions as F sc = SparkContext("local") sqlContext = HiveContext(sc) df = sqlContext.createDataFrame([ ("a", None, None), ("a", "code1", None), ("a", "code2", "name2"), ], ["id", "code", "name"]) df.show() +---+-----+-----+ | id| code| name| +---+-----+---

what&#39;s different between each and collect method in Ruby [duplicate]

由 风流意气都作罢 提交于 2019-11-26 06:29:01
问题 This question already has answers here : Array#each vs. Array#map (6 answers) Closed 3 years ago . From this code I don\'t know the difference between the two methods, collect and each . a = [\"L\",\"Z\",\"J\"].collect{|x| puts x.succ} #=> M AA K print a.class #=> Array b = [\"L\",\"Z\",\"J\"].each{|x| puts x.succ} #=> M AA K print b.class #=> Array 回答1: Array#each takes an array and applies the given block over all items. It doesn't affect the array or creates a new object. It is just a way

pyspark collect_set or collect_list with groupby

由 亡梦爱人 提交于 2019-11-26 04:45:12
问题 How can I use collect_set or collect_list on a dataframe after groupby . for example: df.groupby(\'key\').collect_set(\'values\') . I get an error: AttributeError: \'GroupedData\' object has no attribute \'collect_set\' 回答1: You need to use agg. Example: from pyspark import SparkContext from pyspark.sql import HiveContext from pyspark.sql import functions as F sc = SparkContext("local") sqlContext = HiveContext(sc) df = sqlContext.createDataFrame([ ("a", None, None), ("a", "code1", None), ("a

Extract a dplyr tbl column as a vector

由 試著忘記壹切 提交于 2019-11-26 00:36:58
问题 Is there a more succinct way to get one column of a dplyr tbl as a vector, from a tbl with database back-end (i.e. the data frame/table can\'t be subset directly)? require(dplyr) db <- src_sqlite(tempfile(), create = TRUE) iris2 <- copy_to(db, iris) iris2$Species # NULL That would have been too easy, so collect(select(iris2, Species))[, 1] # [1] \"setosa\" \"setosa\" \"setosa\" \"setosa\" etc. But it seems a bit clumsy. 回答1: With dplyr 0.7.0, you can use pull to get a vector from a tbl .
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