sirenbyte commented on code in PR #23577: URL: https://github.com/apache/beam/pull/23577#discussion_r1132057446
########## learning/tour-of-beam/learning-content/common-transforms/aggregation/count/description.md: ########## @@ -0,0 +1,311 @@ +<!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at +http://www.apache.org/licenses/LICENSE-2.0 +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +# Count + +`Count` provides many transformations for calculating the count of values in a `PCollection`, either globally or for each key. + +{{if (eq .Sdk "go")}} +Counts the number of elements within each aggregation. The Count transform has two varieties: + +You can count the number of elements in a `PCollection` with `CountElms()`, it will return one element. + +``` +import ( + "github.com/apache/beam/sdks/go/pkg/beam" + "github.com/apache/beam/sdks/go/pkg/beam/transforms/stats" +) + +func ApplyTransform(s beam.Scope, input beam.PCollection) beam.PCollection { + return stats.CountElms(s, input) +} +``` + +You can use `Count()` to count how many elements are associated with a particular key. The result will be one output for each key. + +``` +import ( + "github.com/apache/beam/sdks/go/pkg/beam" + "github.com/apache/beam/sdks/go/pkg/beam/transforms/stats" +) + +func ApplyTransform(s beam.Scope, input beam.PCollection) beam.PCollection { + return stats.Count(s, input) +} +``` +{{end}} +{{if (eq .Sdk "java")}} +Counts the number of elements within each aggregation. The Count transform has three varieties: + +### Counting all elements in a PCollection + +`Count.globally()` counts the number of elements in the entire `PCollection`. The result is a collection with a single element. + +``` +PCollection<Integer> input = pipeline.apply(Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)); +PCollection<Long> output = input.apply(Count.globally()); +``` + +Output +``` +10 +``` + +### Counting elements for each key + +`Count.perKey()` counts how many elements are associated with each key. It ignores the values. The resulting collection has one output for every key in the input collection. + +``` +PCollection<KV<String, Integer>> input = pipeline.apply( + Create.of(KV.of("🥕", 3), + KV.of("🥕", 2), + KV.of("🍆", 1), + KV.of("🍅", 4), + KV.of("🍅", 5), + KV.of("🍅", 3))); +PCollection<KV<String, Long>> output = input.apply(Count.perKey()); +``` + +Output + +``` +KV{🥕, 2} +KV{🍅, 3} +KV{🍆, 1} +``` + +### Counting all unique elements + +`Count.perElement()` counts how many times each element appears in the input collection. The output collection is a key-value pair, containing each unique element and the number of times it appeared in the original collection. + +``` +PCollection<KV<String, Integer>> input = pipeline.apply( + Create.of(KV.of("🥕", 3), + KV.of("🥕", 2), + KV.of("🍆", 1), + KV.of("🍅", 3), + KV.of("🍅", 5), + KV.of("🍅", 3))); +PCollection<KV<String, Long>> output = input.apply(Count.perElement()); +``` + +Output + +``` +KV{KV{🍅, 3}, 2} +KV{KV{🥕, 2}, 1} +KV{KV{🍆, 1}, 1} +KV{KV{🥕, 3}, 1} +KV{KV{🍅, 5}, 1} +``` +{{end}} +{{if (eq .Sdk "python")}} +### Counting all elements in a PCollection + +You can use `Count.Globally()` to count all elements in a PCollection, even if there are duplicate elements. + +``` +import apache_beam as beam + +with beam.Pipeline() as p: + total_elements = ( + p Review Comment: Done ########## learning/tour-of-beam/learning-content/common-transforms/aggregation/count/description.md: ########## @@ -0,0 +1,311 @@ +<!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at +http://www.apache.org/licenses/LICENSE-2.0 +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +# Count + +`Count` provides many transformations for calculating the count of values in a `PCollection`, either globally or for each key. + +{{if (eq .Sdk "go")}} +Counts the number of elements within each aggregation. The Count transform has two varieties: + +You can count the number of elements in a `PCollection` with `CountElms()`, it will return one element. + +``` +import ( + "github.com/apache/beam/sdks/go/pkg/beam" + "github.com/apache/beam/sdks/go/pkg/beam/transforms/stats" +) + +func ApplyTransform(s beam.Scope, input beam.PCollection) beam.PCollection { + return stats.CountElms(s, input) +} +``` + +You can use `Count()` to count how many elements are associated with a particular key. The result will be one output for each key. + +``` +import ( + "github.com/apache/beam/sdks/go/pkg/beam" + "github.com/apache/beam/sdks/go/pkg/beam/transforms/stats" +) + +func ApplyTransform(s beam.Scope, input beam.PCollection) beam.PCollection { + return stats.Count(s, input) +} +``` +{{end}} +{{if (eq .Sdk "java")}} +Counts the number of elements within each aggregation. The Count transform has three varieties: + +### Counting all elements in a PCollection + +`Count.globally()` counts the number of elements in the entire `PCollection`. The result is a collection with a single element. + +``` +PCollection<Integer> input = pipeline.apply(Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)); +PCollection<Long> output = input.apply(Count.globally()); +``` + +Output +``` +10 +``` + +### Counting elements for each key + +`Count.perKey()` counts how many elements are associated with each key. It ignores the values. The resulting collection has one output for every key in the input collection. + +``` +PCollection<KV<String, Integer>> input = pipeline.apply( + Create.of(KV.of("🥕", 3), + KV.of("🥕", 2), + KV.of("🍆", 1), + KV.of("🍅", 4), + KV.of("🍅", 5), + KV.of("🍅", 3))); +PCollection<KV<String, Long>> output = input.apply(Count.perKey()); +``` + +Output + +``` +KV{🥕, 2} +KV{🍅, 3} +KV{🍆, 1} +``` + +### Counting all unique elements + +`Count.perElement()` counts how many times each element appears in the input collection. The output collection is a key-value pair, containing each unique element and the number of times it appeared in the original collection. + +``` +PCollection<KV<String, Integer>> input = pipeline.apply( + Create.of(KV.of("🥕", 3), + KV.of("🥕", 2), + KV.of("🍆", 1), + KV.of("🍅", 3), + KV.of("🍅", 5), + KV.of("🍅", 3))); +PCollection<KV<String, Long>> output = input.apply(Count.perElement()); +``` + +Output + +``` +KV{KV{🍅, 3}, 2} +KV{KV{🥕, 2}, 1} +KV{KV{🍆, 1}, 1} +KV{KV{🥕, 3}, 1} +KV{KV{🍅, 5}, 1} +``` +{{end}} +{{if (eq .Sdk "python")}} +### Counting all elements in a PCollection + +You can use `Count.Globally()` to count all elements in a PCollection, even if there are duplicate elements. + +``` +import apache_beam as beam + +with beam.Pipeline() as p: + total_elements = ( + p + | 'Create plants' >> beam.Create( + ['🍓', '🥕', '🥕', '🥕', '🍆', '🍆', '🍅', '🍅', '🍅', '🌽']) + | 'Count all elements' >> beam.combiners.Count.Globally() + | beam.Map(print)) +``` + +Output + +``` +10 +``` + +### Counting elements for each key + +You can use `Count.PerKey()` to count the elements for each unique key in a PCollection of key-values. + +``` +import apache_beam as beam + +with beam.Pipeline() as p: + total_elements_per_keys = ( + p Review Comment: Done ########## learning/tour-of-beam/learning-content/common-transforms/aggregation/count/description.md: ########## @@ -0,0 +1,311 @@ +<!-- +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at +http://www.apache.org/licenses/LICENSE-2.0 +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. +--> + +# Count + +`Count` provides many transformations for calculating the count of values in a `PCollection`, either globally or for each key. + +{{if (eq .Sdk "go")}} +Counts the number of elements within each aggregation. The Count transform has two varieties: + +You can count the number of elements in a `PCollection` with `CountElms()`, it will return one element. + +``` +import ( + "github.com/apache/beam/sdks/go/pkg/beam" + "github.com/apache/beam/sdks/go/pkg/beam/transforms/stats" +) + +func ApplyTransform(s beam.Scope, input beam.PCollection) beam.PCollection { + return stats.CountElms(s, input) +} +``` + +You can use `Count()` to count how many elements are associated with a particular key. The result will be one output for each key. + +``` +import ( + "github.com/apache/beam/sdks/go/pkg/beam" + "github.com/apache/beam/sdks/go/pkg/beam/transforms/stats" +) + +func ApplyTransform(s beam.Scope, input beam.PCollection) beam.PCollection { + return stats.Count(s, input) +} +``` +{{end}} +{{if (eq .Sdk "java")}} +Counts the number of elements within each aggregation. The Count transform has three varieties: + +### Counting all elements in a PCollection + +`Count.globally()` counts the number of elements in the entire `PCollection`. The result is a collection with a single element. + +``` +PCollection<Integer> input = pipeline.apply(Create.of(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)); +PCollection<Long> output = input.apply(Count.globally()); +``` + +Output +``` +10 +``` + +### Counting elements for each key + +`Count.perKey()` counts how many elements are associated with each key. It ignores the values. The resulting collection has one output for every key in the input collection. + +``` +PCollection<KV<String, Integer>> input = pipeline.apply( + Create.of(KV.of("🥕", 3), + KV.of("🥕", 2), + KV.of("🍆", 1), + KV.of("🍅", 4), + KV.of("🍅", 5), + KV.of("🍅", 3))); +PCollection<KV<String, Long>> output = input.apply(Count.perKey()); +``` + +Output + +``` +KV{🥕, 2} +KV{🍅, 3} +KV{🍆, 1} +``` + +### Counting all unique elements + +`Count.perElement()` counts how many times each element appears in the input collection. The output collection is a key-value pair, containing each unique element and the number of times it appeared in the original collection. + +``` +PCollection<KV<String, Integer>> input = pipeline.apply( + Create.of(KV.of("🥕", 3), + KV.of("🥕", 2), + KV.of("🍆", 1), + KV.of("🍅", 3), + KV.of("🍅", 5), + KV.of("🍅", 3))); +PCollection<KV<String, Long>> output = input.apply(Count.perElement()); +``` + +Output + +``` +KV{KV{🍅, 3}, 2} +KV{KV{🥕, 2}, 1} +KV{KV{🍆, 1}, 1} +KV{KV{🥕, 3}, 1} +KV{KV{🍅, 5}, 1} +``` +{{end}} +{{if (eq .Sdk "python")}} +### Counting all elements in a PCollection + +You can use `Count.Globally()` to count all elements in a PCollection, even if there are duplicate elements. + +``` +import apache_beam as beam + +with beam.Pipeline() as p: + total_elements = ( + p + | 'Create plants' >> beam.Create( + ['🍓', '🥕', '🥕', '🥕', '🍆', '🍆', '🍅', '🍅', '🍅', '🌽']) + | 'Count all elements' >> beam.combiners.Count.Globally() + | beam.Map(print)) +``` + +Output + +``` +10 +``` + +### Counting elements for each key + +You can use `Count.PerKey()` to count the elements for each unique key in a PCollection of key-values. + +``` +import apache_beam as beam + +with beam.Pipeline() as p: + total_elements_per_keys = ( + p + | 'Create plants' >> beam.Create([ + ('spring', '🍓'), + ('spring', '🥕'), + ('summer', '🥕'), + ('fall', '🥕'), + ('spring', '🍆'), + ('winter', '🍆'), + ('spring', '🍅'), + ('summer', '🍅'), + ('fall', '🍅'), + ('summer', '🌽'), + ]) + | 'Count elements per key' >> beam.combiners.Count.PerKey() + | beam.Map(print)) +``` + +Output + +``` +('spring', 4) +('summer', 3) +('fall', 2) +('winter', 1) +``` + +### Counting all unique elements + +You can use `Count.PerElement()` to count only the unique elements in a `PCollection`. + +``` +import apache_beam as beam + +with beam.Pipeline() as p: + total_unique_elements = ( + p Review Comment: Done -- This is an automated message from the Apache Git Service. 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