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docs: update markdown format(markdownlint-cli2)
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.github/PULL_REQUEST_TEMPLATE.md

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exercises/practice/parallel-letter-frequency/.approaches/fork-join/content.md

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If there are no strings, a validation step prevents unnecessary processing.
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A [`ForkJoinPool`][ForkJoinPool] is then created.
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A [`ForkJoinPool`][ForkJoinPool] is then created.
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The core of [`ForkJoinPool`][ForkJoinPool] is the Fork/Join mechanism, which divides tasks into smaller units and processes them in parallel.
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THRESHOLD is the criterion for task division.
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THRESHOLD is the criterion for task division.
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If the range of texts exceeds the THRESHOLD, the task is divided into two subtasks, and [`invokeAll`][invokeAll](leftTask, rightTask) is called to execute both tasks in parallel.
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Each subtask in LetterCountTask will continue calling compute() to divide itself further until the range is smaller than or equal to the threshold.
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For tasks that are within the threshold, letter frequency is calculated.
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For tasks that are within the threshold, letter frequency is calculated.
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The [`Character.isAlphabetic`][isAlphabetic] method is used to identify all characters classified as alphabetic in Unicode, covering various languages like English, Korean, Japanese, Chinese, etc., returning true for alphabetic characters and false for numbers, special characters, spaces, and others.
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exercises/practice/parallel-letter-frequency/.approaches/introduction.md

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If the data being counted has a limited range (e.g., characters or integers), an `int[] array` or [`List<Integer>`][list] can be used to record frequencies.
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Parallel processing typically takes place in a multi-[`thread`][thread] environment.
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Parallel processing typically takes place in a multi-[`thread`][thread] environment.
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The Java 8 [`stream`][stream] API provides methods that make parallel processing easier, including the parallelStream() method.
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The Java 8 [`stream`][stream] API provides methods that make parallel processing easier, including the parallelStream() method.
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With parallelStream(), developers can use the ForkJoinPool model for workload division and parallel execution, without the need to manually manage threads or create custom thread pools.
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The [`ForkJoinPool`][ForkJoinPool] class, optimized for dividing and managing tasks, makes parallel processing efficient.
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However, parallelStream() uses the common ForkJoinPool by default, meaning multiple parallelStream instances share the same thread pool unless configured otherwise.
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However, parallelStream() uses the common ForkJoinPool by default, meaning multiple parallelStream instances share the same thread pool unless configured otherwise.
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As a result, parallel streams may interfere with each other when sharing this thread pool, potentially affecting performance.
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Although this doesn’t directly impact solving the Parallel Letter Frequency problem, it may introduce issues when thread pool sharing causes conflicts in other applications.
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Although this doesn’t directly impact solving the Parallel Letter Frequency problem, it may introduce issues when thread pool sharing causes conflicts in other applications.
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Therefore, a custom ForkJoinPool approach is also provided below.
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exercises/practice/parallel-letter-frequency/.approaches/parallel-stream/content.md

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If there are no strings to process, a validation step avoids unnecessary computation.
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To calculate letter frequency, a parallel stream is used.
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To calculate letter frequency, a parallel stream is used.
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The [`Character.isAlphabetic`][isAlphabetic] method identifies all characters classified as alphabetic in Unicode, covering characters from various languages like English, Korean, Japanese, Chinese, etc., returning true. Non-alphabetic characters, including numbers, special characters, and spaces, return false.
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