[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-09-04 (世界標準時間)。"],[[["\u003cp\u003eThis guide outlines the process of separating data within a single cell into multiple rows using the Wrangler workspace in Cloud Data Fusion Studio.\u003c/p\u003e\n"],["\u003cp\u003eThe "Explode > Delimited text" feature allows users to split values within a cell into new rows based on delimiters such as commas, tabs, pipes, whitespace, or a custom separator defined with a regular expression.\u003c/p\u003e\n"],["\u003cp\u003eWhen splitting delimited text, if a cell does not contain the specified delimiter, no new row will be inserted, and the original column is deleted and replaced by a new one.\u003c/p\u003e\n"],["\u003cp\u003eThe "flatten" directive can be used to separate array items into new rows, while also copying the other column values from the original record into each new record.\u003c/p\u003e\n"],["\u003cp\u003eThe \u003ccode\u003esplit-to-row\u003c/code\u003e directive is added to the recipe when using the delimited text feature, applying the transformation to all values in the column when the data pipeline runs.\u003c/p\u003e\n"]]],[],null,["# Explode data from fields\n\nThis page explains how to separate data from a field (a cell) into multiple\nrows when you prepare data in the Wrangler workspace of the Cloud Data Fusion\nStudio.\n\nSeparate delimited text\n-----------------------\n\nYou can separate the values from a cell into new rows if the values are\nseparated by the following delimiters:\n\n- Comma\n- Tab\n- Pipe\n- Whitespace\n- Custom separator\n\nIf a cell doesn't contain the chosen delimiter, no new row is inserted.\n\nTo split values based on a delimiter, follow these steps:\n\n1. [Go to Wrangler workspace in Cloud Data Fusion](/data-fusion/docs/concepts/wrangler-overview#navigate-to-wrangler).\n2. On the **Data** tab, go to a column name and click the arrow_drop_down expander arrow.\n3. Click **Explode \\\u003e Delimited text**.\n4. Choose a delimiter---for example **Pipe**.\n5. Click **Extract**.\n\n | **Note:** If you select Custom separator, define the delimiter with a regular expression.\n\nWrangler splits the fields based on the selected delimiter and adds the\n`split-to-row` directive to the recipe. When you run the data pipeline,\nCloud Data Fusion applies the transformation to all values in the column.\n\nIn this example, a dataset has a column of string values containing the comma\ndelimiter:\n\nTo divide the value into separate rows, Wrangler deletes the original column and\ncreates a new column with one row for each value. The other column values from\nthe original row are copied into the new rows:\n\nSeparate arrays\n---------------\n\nThe `flatten` directive separates items in arrays, such as `[\"ELEMENT_1\",\n\"ELEMENT_2\", \"ELEMENT_3\"]`, into new rows. The other column values from the\noriginal record are copied into the new records.\n\nWhat's next\n-----------\n\n- Learn more about [Wrangler directives](/data-fusion/docs/concepts/wrangler-overview#apply_directives)."]]
