Streams are convenient way to reduce the line of codes, but an understanding them is equally challenging. I write this blog, after realising a desperate attempt at solving a trivial problem just took overwhelming time. (Could be that I am getting old, but never late to learn things again)<\/p>\n
\u00a0<\/p>\n\n\n
public class PlaySteams {\n public static void main(String []args) {\n int[] a = new int[] {1,1,1,2,2,2,3,3,3,4,4,4};\n \/\/Stream Sum of the array\n long sum = IntStream.range(0, a.length).count();\n\n System.out.printf(\"Sum: %d\\n\", sum);\n \/\/ Maximum\n System.out.printf(\"Max: %d\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().max().getAsInt());\n \/\/ Minimum\n System.out.printf(\"Min: %d\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().min().getAsInt());\n\n IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().forEach(x -> System.out.printf(\"%d \", x));\n System.out.printf(\"Average (Distinct): %f\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().average().getAsDouble());\n\n System.out.printf(\" Number of elements : %d\\n\", IntStream.of(a).asLongStream().count());\n\n IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).forEach(x -> System.out.printf(\"%d \", x));\n System.out.printf(\"Average (All): %f\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).average().getAsDouble());\n\n List<Integer> listOfIntegers = IntStream.of(a).boxed().collect(Collectors.toList());\n System.out.println(listOfIntegers.toString());\n\n System.out.println(\"Length: \");\n System.out.println(listOfIntegers.size());\n\n \/\/ Creating a map\n \/\/ 1 -> 3\n \/\/ 2 -> 3 ...\n System.out.println(IntStream.range(0, a.length).map(i -> a[i]).boxed().collect(Collectors.groupingBy(Function.identity(), Collectors.counting())).toString());\n\n \/\/ Using list\n Map<Integer, Long> valueMap = listOfIntegers.stream().collect(Collectors.groupingBy(Function.identity(), Collectors.counting()));\n System.out.println(valueMap.toString());\n\n \/\/ Map of indexes\n \/\/ Indexes and value of the index\n System.out.println(IntStream.range(0, a.length).boxed().collect(Collectors.groupingBy( i -> a[Integer.valueOf(i)], Collectors.toList())));\n\n\n }\n}<\/code><\/pre>\n\n\n\nThe example set remains the same for all the invocation.<\/p>\n\n\n\n
int[] a = new int[] {1,1,1,2,2,2,3,3,3,4,4,4};<\/code><\/pre>\n\n\n\nExample – 1:<\/h2>\n\n\n\nlong sum = IntStream.range(0, a.length).count();\nSystem.out.printf(\"Sum: %d\\n\", sum);<\/code><\/pre>\n\n\n\nIt simply runs over the length of the array and returns the total number of elements<\/p>\n\n\n\n
Sum: 12<\/code><\/pre>\n\n\n\nExample – 2:<\/h2>\n\n\n\n
Return the maximum<\/p>\n\n\n\n
System.out.printf(\"Max: %d\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().max().getAsInt());<\/code><\/pre>\n\n\n\nMax: 4<\/code><\/pre>\n\n\n\nExample – 3:<\/h2>\n\n\n\n
Returns the minimum<\/p>\n\n\n\n
System.out.printf(\"Min: %d\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().min().getAsInt());<\/code><\/pre>\n\n\n\nMin: 1<\/code><\/pre>\n\n\n\nExample – 4:<\/h2>\n\n\n\n
Run through the list and print distinct items<\/p>\n\n\n\n
IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().forEach(\nx -> \nSystem.out.printf(\"%d \", x));<\/code><\/pre>\n\n\n\n1 2 3 4 <\/code><\/pre>\n\n\n\nExample – 5:<\/h2>\n\n\n\n
Average of the distinct items<\/p>\n\n\n\n
System.out.printf(\"Average (Distinct): %f\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).distinct().average().getAsDouble());<\/code><\/pre>\n\n\n\nAverage (Distinct): 2.500000<\/code><\/pre>\n\n\n\nExample – 6:<\/h2>\n\n\n\n
Different way of getting the count of elements.<\/p>\n\n\n\n
System.out.printf(\" Number of elements : %d\\n\", IntStream.of(a).asLongStream().count());<\/code><\/pre>\n\n\n\nNumber of elements : 12<\/code><\/pre>\n\n\n\nExample – 7:<\/h2>\n\n\n\nIntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).forEach(x -> System.out.printf(\"%d \", x));<\/code><\/pre>\n\n\n\nGet the list of elements<\/p>\n\n\n\n
1 1 1 2 2 2 3 3 3 4 4 4 <\/code><\/pre>\n\n\n\nExample – 8:<\/h2>\n\n\n\nSystem.out.printf(\"Average (All): %f\\n\", IntStream.range(0, a.length).map(i -> Integer.valueOf(a[i])).average().getAsDouble());<\/code><\/pre>\n\n\n\nAverage (All): 2.500000<\/code><\/pre>\n\n\n\nExample – 9:<\/h2>\n\n\n\nList<Integer> listOfIntegers = IntStream.of(a).boxed().collect(Collectors.toList());\nSystem.out.println(listOfIntegers.toString());<\/code><\/pre>\n\n\n\n[1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4]<\/code><\/pre>\n\n\n\nExample – 10:<\/h2>\n\n\n\nSystem.out.println(IntStream.range(0, a.length).map(i -> a[i]).boxed().collect(Collectors.groupingBy(Function.identity(), Collectors.counting())).toString());<\/code><\/pre>\n\n\n\nCreates a map of the value and the number of times it repeats<\/p>\n\n\n\n
1=3, 2=3, 3=3, 4=3}<\/code><\/pre>\n\n\n\nExample – 11:<\/h2>\n\n\n\nMap<Integer, Long> valueMap = listOfIntegers.stream().collect(Collectors.groupingBy(Function.identity(), Collectors.counting()));\n System.out.println(valueMap.toString());<\/code><\/pre>\n\n\n\nUsing list that we had in Example - 9<\/code> to get the map.<\/p>\n\n\n\n{1=3, 2=3, 3=3, 4=3}<\/code><\/pre>\n\n\n\nExample – 12:<\/h2>\n\n\n\n
Returns the list of index for each value<\/p>\n\n\n\n
System.out.println(IntStream.range(0, a.length).boxed().collect(Collectors.groupingBy( i -> a[Integer.valueOf(i)], Collectors.toList())));<\/code><\/pre>\n\n\n\n{1=[0, 1, 2], 2=[3, 4, 5], 3=[6, 7, 8], 4=[9, 10, 11]}<\/code><\/pre>\n\n\n\n<\/p>\n","protected":false},"excerpt":{"rendered":"
Streams are convenient way to reduce the line of codes, but an understanding them is equally challenging. I write this blog, after realising a desperate attempt at solving a trivial problem just took overwhelming time. (Could be that I am getting old, but never late to learn things again) \u00a0 The example set remains the […]<\/p>\n","protected":false},"author":2,"featured_media":1396,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"image","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"categories":[120,34],"tags":[122],"class_list":["post-1510","post","type-post","status-publish","format-image","has-post-thumbnail","hentry","category-java","category-technical","tag-streams","post_format-post-format-image"],"_links":{"self":[{"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/posts\/1510","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/comments?post=1510"}],"version-history":[{"count":0,"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/posts\/1510\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/media\/1396"}],"wp:attachment":[{"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/media?parent=1510"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/categories?post=1510"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.samarthya.me\/wps\/wp-json\/wp\/v2\/tags?post=1510"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}