bucket 0

c++ unordered_map

unordered_map,unordered_map,buckets,()unordered_mapmap(operator[])forward iterators

unordered_mapunordered_map:(1)()unordered_map0hasherkey_equal(2)rangeunordered_map[first,last)(3)()unordered_mapump(4)()rvalueump(5)

ump(il)unordered_map umpil()(1)ump(ump)(2)ump:ump(3)il

(1)(2)(iteratorconst_iteratorlocal_iteratorconst_local_iterator)unordered_mapvalue_typediffence_type

unordered_map(1)(2)past-the-endendunordered_map()[begin,end]unordered_map()

(1)(2)(iteratorconst_iteratorlocal_iteratorconst_local_iterator)unordered_mapvalue_typediffence_type

const_iteratorconst_iteratorunordered_map(1)(2)past-the-endcendconst_iteratorunordered_mappast-the-endbucket(past-the-end)[cbegin,cend)unordered_mapcbegincend(bucket)const_iteratorconst(const)unordered_map::end

()pairtruepairfalseallocator_traits::construct()(bad_alloc)

unordered_mapargsposition()(unordered_map)1insert

umpumpunordered_mapumpump(hasherkey_equal)swapunordered_map

unordered_map()(bucket_count):load_factor = size / bucket_count)(max_load_factor)max_load_factor

(1)unordered_map(2)zunordered_map()(bucket_count)unordered_mapmax_load_factor1.0)max_load_factor()(max_bucket_count)max_load_factor

nn(bucket_count)bucket countnn(bucket_count)rehash:bucketmax_load_factorunordered_map::reserve

unordered_mapunordered_maplhsrhs():unordered_map::hash_functionunordered_map::key_eqlhsrhs

unordered_maplhsrhs()lhsrhsrhslhs(hasherkey_equal)swap

hive bucket - charlist00

Total MapReduce jobs = 1Launching Job 1 out of 1.......OK4 18 mac 201208022 21 ljz 201208026 23 symbian 20120802Time taken: 20.608 secondstablesampleTABLESAMPLE(BUCKET x OUT OF y)ytablebuckethiveytable64y=32(64/32=)2buckety=128(64/128=)1/2bucketxbuckettablebucket32tablesample(bucket 3 out of 16)32/16=2bucket3bucket3+16=19bucket

c++stlunordered_map

==========================================begin iteratorend cbegin const_iteratorcend =================Capacity================size max_size unordered_map empty ==================================operator[] at ==================================insert erase swap clear emplace emplace_hint =========================================find ,unordered_map::endcount equal_range ================Buckets======================bucket_count Bucketmax_bucket_count bucket_size bucket load_factor Bucketmax_load_factor rehashreserve

cephrgw_dynamic_resharding - luxf0

https://access.redhat.com/documentation/en-us/red_hat_ceph_storage/2/html/object_gateway_guide_for_ubuntu/administration_cli#configuring-bucket-index-sharding https://ceph.com/community/new-luminous-rgw-dynamic-bucket-sharding/

javabucket sort)

JAVA import java.util.ArrayList; import java.util.Arrays; import java.util.Collections; import java.util.List; /* * Java * input: [80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50] * output: [0, 10, 20, 30, 40, 50, 50, 60, 70, 80, 90] * * : * On; On; On ^ 2 * */ public class BuckeSort { public static void main(String args) { System.out.println("Bucket sort in Java"); int input = { 80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50 }; System.out.println("integer array before sorting"); System.out.println(Arrays.toString(input)); // sorting array using radix Sort Algorithm bucketSort(input); System.out.println("integer array after sorting using bucket sort algorithm"); System.out.println(Arrays.toString(input)); } /** * * @param input */ public static void bucketSort(int input) { // get hash codes final int code = hash(input); // create and initialize buckets to ArrayList: O(n) List buckets = new List[code[1]]; for (int i = 0; i < code[1]; i++) { buckets[i] = new ArrayList(); } // distribute data into buckets: O(n) for (int i : input) { buckets[hash(i, code)].add(i); } // sort each bucket O(n) for (List bucket : buckets) { Collections.sort(bucket); } int ndx = 0; // merge the buckets: O(n) for (int b = 0; b < buckets.length; b++) { for (int v : buckets[b]) { [/b][/i] input[ndx++] = v; } } } /** * * @param input * @return an array containing hash of input */ private static int hash(int input) { int m = input[0]; for (int i = 1; i < input.length; i++) { if (m < input) { m = input; } } return new int { m, (int) Math.sqrt(input.length) }; } /** * * @param i * @param code * @return */ private static int hash(int i, int code) { return (int) ((double) i / code[0] * (code[1] - 1)); } } Output Bucket sort in Java integer array before sorting

[80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50] integer array after sorting using bucket sort algorithm

[0, 10, 20, 30, 40, 50, 50, 60, 70, 80, 90] 1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

import java.util.ArrayList; import java.util.Arrays; import java.util.Collections; import java.util.List; /* * Java * input: [80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50] * output: [0, 10, 20, 30, 40, 50, 50, 60, 70, 80, 90] * * : * On; On; On ^ 2 * */ public class BuckeSort { public static void main(String args) { System.out.println("Bucket sort in Java"); int input = { 80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50 }; System.out.println("integer array before sorting"); System.out.println(Arrays.toString(input)); // sorting array using radix Sort Algorithm bucketSort(input); System.out.println("integer array after sorting using bucket sort algorithm"); System.out.println(Arrays.toString(input)); } /** * * @param input */ public static void bucketSort(int input) { // get hash codes final int code = hash(input); // create and initialize buckets to ArrayList: O(n) List buckets = new List[code[1]]; for (int i = 0; i < code[1]; i++) { buckets[i] = new ArrayList(); } // distribute data into buckets: O(n) for (int i : input) { buckets[hash(i, code)].add(i); } // sort each bucket O(n) for (List bucket : buckets) { Collections.sort(bucket); } int ndx = 0; // merge the buckets: O(n) for (int b = 0; b < buckets.length; b++) { for (int v : buckets[b]) { [/b][/i] input[ndx++] = v; } } } /** * * @param input * @return an array containing hash of input */ private static int hash(int input) { int m = input[0]; for (int i = 1; i < input.length; i++) { if (m < input) { m = input; } } return new int { m, (int) Math.sqrt(input.length) }; } /** * * @param i * @param code * @return */ private static int hash(int i, int code) { return (int) ((double) i / code[0] * (code[1] - 1)); } } Output Bucket sort in Java integer array before sorting

[80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50] integer array after sorting using bucket sort algorithm

[0, 10, 20, 30, 40, 50, 50, 60, 70, 80, 90] 1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

import java.util.ArrayList; import java.util.Arrays; import java.util.Collections; import java.util.List; /* * Java * input: [80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50] * output: [0, 10, 20, 30, 40, 50, 50, 60, 70, 80, 90] * * : * On; On; On ^ 2 * */ public class BuckeSort { public static void main(String args) { System.out.println("Bucket sort in Java"); int input = { 80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50 }; System.out.println("integer array before sorting"); System.out.println(Arrays.toString(input)); // sorting array using radix Sort Algorithm bucketSort(input); System.out.println("integer array after sorting using bucket sort algorithm"); System.out.println(Arrays.toString(input)); } /** * * @param input */ public static void bucketSort(int input) { // get hash codes final int code = hash(input); // create and initialize buckets to ArrayList: O(n) List buckets = new List[code[1]]; for (int i = 0; i < code[1]; i++) { buckets[i] = new ArrayList(); } // distribute data into buckets: O(n) for (int i : input) { buckets[hash(i, code)].add(i); } // sort each bucket O(n) for (List bucket : buckets) { Collections.sort(bucket); } int ndx = 0; // merge the buckets: O(n) for (int b = 0; b < buckets.length; b++) { for (int v : buckets[b]) { [/b][/i] input[ndx++] = v; } } } /** * * @param input * @return an array containing hash of input */ private static int hash(int input) { int m = input[0]; for (int i = 1; i < input.length; i++) { if (m < input) { m = input; } } return new int { m, (int) Math.sqrt(input.length) }; } /** * * @param i * @param code * @return */ private static int hash(int i, int code) { return (int) ((double) i / code[0] * (code[1] - 1)); } } Output Bucket sort in Java integer array before sorting

[80, 50, 30, 10, 90, 60, 0, 70, 40, 20, 50] integer array after sorting using bucket sort algorithm

[0, 10, 20, 30, 40, 50, 50, 60, 70, 80, 90] 1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

1Bucket Sortbin sortBucketbin2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

2Bucket110034bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

34bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

4bucketONbucketquicksortmergesortNLogN5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

5Bucket 6bucketbucket7Bucket8BucketOn ^ 29bucketon

6bucketbucket7Bucket8BucketOn ^ 29bucketon

$bucket (aggregation) mongodb manual

Categorizes incoming documents into groups, called buckets, based on a specified expression and bucket boundaries and outputs a document per each bucket. Each output document contains an _id field whose value specifies the inclusive lower bound of the bucket. The output option specifies the fields included in each output document.

The $bucket stage has a limit of 100 megabytes of RAM. By default, if the stage exceeds this limit, $bucket returns an error. To allow more space for stage processing, use the allowDiskUse option to enable aggregation pipeline stages to write data to temporary files.

An array of values based on the groupBy expression that specify the boundaries for each bucket. Each adjacent pair of values acts as the inclusive lower boundary and the exclusive upper boundary for the bucket. You must specify at least two boundaries.