Mengganti nama, menyalin, menghapus, atau mempertahankan kolom
Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Halaman ini menjelaskan cara mengganti nama, menyalin, menghapus, atau mempertahankan kolom saat Anda menyiapkan data di ruang kerja Wrangler di Cloud Data Fusion Studio.
Mengganti nama kolom
Untuk mengganti nama kolom di ruang kerja Wrangler, klik nama kolom, lalu masukkan nama baru. Wrangler menambahkan perintah rename ke resep.
Menyalin kolom
Untuk memahami dampak penggunaan perintah baru pada set data, Anda dapat menyalin
kolom ke kolom baru dengan nama yang berbeda dan menerapkan perintah di sana.
Untuk menyalin kolom, ikuti langkah-langkah berikut:
Di tab Data, buka nama kolom, lalu klik panah peluas arrow_drop_down.
Pilih Salin kolom, lalu masukkan nama untuk kolom baru.
Wrangler menyalin kolom dan menambahkan perintah copy ke resep.
Menghapus kolom
Untuk set data dengan banyak kolom, Anda dapat meningkatkan performa pipeline dan menghemat
resource dengan menghapus kolom yang tidak diperlukan. Dengan lebih sedikit kolom, pipeline
akan selesai lebih cepat. Hal ini terutama berlaku untuk pipeline yang menyertakan
transformasi Joiner.
Untuk menghapus kolom dari set data, ikuti langkah-langkah berikut:
[[["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 details how to manage columns within the Cloud Data Fusion Wrangler workspace, including renaming, copying, deleting, and keeping columns.\u003c/p\u003e\n"],["\u003cp\u003eRenaming a column is done by clicking on the column name and entering the new one, which will add the \u003ccode\u003erename\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"],["\u003cp\u003eCopying a column involves using the "Copy column" option from the column's dropdown, which then allows you to apply directives to a duplicated column, adding the \u003ccode\u003ecopy\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"],["\u003cp\u003eDeleting a column is done via the "Delete column" option, reducing the dataset's size and improving pipeline efficiency, and this adds the \u003ccode\u003edrop\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"],["\u003cp\u003eThe "Keep column" feature deletes all columns except the selected one, making it possible to quickly isolate a single column, which adds the \u003ccode\u003ekeep\u003c/code\u003e directive to the recipe.\u003c/p\u003e\n"]]],[],null,["# Rename, copy, delete, or keep columns\n\nThis page explains how to rename, copy, delete, or keep columns when you prepare\ndata in the Wrangler workspace of the Cloud Data Fusion Studio.\n\nRename a column\n---------------\n\nTo rename a column in the Wrangler workspace, click a column name and enter a\nnew name. Wrangler adds the `rename` directive to the recipe.\n\nCopy a column\n-------------\n\nTo understand the impact of using a new directive on a dataset, you can copy a\ncolumn into a new column with a different name and apply directives there.\n\nTo copy a column, 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. Select **Copy column** and enter a name for the new column.\n\nWrangler copies the column and adds the `copy` directive to the recipe.\n\nDelete a column\n---------------\n\nFor datasets with many columns, you can improve pipeline performance and save\nresources by deleting unnecessary columns. With fewer columns, the pipeline\nrun completes faster. This is especially true for pipelines that include a\nJoiner transformation.\n\nTo delete a column from a dataset, 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. Select **Delete column**.\n\nWrangler deletes the column and adds the `drop` directive to the recipe.\n\nKeep a column\n-------------\n\nYou can keep a column in a dataset and delete all other columns.\n\nTo keep a column, 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. Select **Keep column**.\n\nWrangler deletes all columns in the dataset, except the one you chose, and adds\nthe `keep` directive to the recipe.\n\nWhat's next\n-----------\n\n- Learn more about [Wrangler directives](/data-fusion/docs/concepts/wrangler-overview#apply_directives)."]]
