Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Halaman ini menjelaskan cara memisahkan data dari kolom (sel) menjadi beberapa
baris saat Anda menyiapkan data di ruang kerja Wrangler di Cloud Data Fusion
Studio.
Memisahkan teks yang dibatasi
Anda dapat memisahkan nilai dari sel ke baris baru jika nilai tersebut
dipisahkan oleh pemisah berikut:
Koma
Tab
Pipe
Spasi Kosong
Pemisah kustom
Jika sel tidak berisi pemisah yang dipilih, baris baru tidak akan disisipkan.
Untuk memisahkan nilai berdasarkan pemisah, ikuti langkah-langkah berikut:
Di tab Data, buka nama kolom, lalu klik panah peluas arrow_drop_down.
Klik Explode > Delimited text.
Pilih pemisah—misalnya Pipa.
Klik Ekstrak.
Wrangler membagi kolom berdasarkan pemisah yang dipilih dan menambahkan
perintah split-to-row ke resep. Saat Anda menjalankan pipeline data,
Cloud Data Fusion akan menerapkan transformasi ke semua nilai dalam kolom.
Dalam contoh ini, set data memiliki kolom nilai string yang berisi pemisah
koma:
ID
Nama
1
Lee,Lucian,Luka
2
Mahan,Noam
Untuk membagi nilai menjadi baris terpisah, Wrangler akan menghapus kolom asli dan membuat kolom baru dengan satu baris untuk setiap nilai. Nilai kolom lainnya dari
baris asli disalin ke baris baru:
ID
Name_1
1
Lee
1
Lucian
1
Luka
2
Mahan
2
Noam
Array terpisah
Perintah flatten memisahkan item dalam array, seperti ["ELEMENT_1",
"ELEMENT_2", "ELEMENT_3"], menjadi baris baru. Nilai kolom lainnya dari
data asli disalin ke data baru.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[[["\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)."]]
