How to import data from Amazon S3?

Import data from Amazon S3




Zoho DataPrep supports importing data from Amazon S3 cloud storage service. Amazon Simple Storage Service, also known as Amazon S3 from AWS provides object storage through a web service interface.

Info
Important 
Prior to connecting your Amazon S3 data with Zoho DataPrep, you need to enable the below permissions from your Amazon S3 account:
1. ListAllMyBuckets
2. Get BucketLocation
3. ListBucket
4. GetObject
Please refer to Amazon S3 help pages to provide these permissions. 

To import data from Amazon S3

1. Open an existing pipeline or create a pipeline from the Home Page, Pipelines tab or Workspaces tab and click the Add data option.
InfoInfo: You can also click the Import data  icon at the top of the pipeline builder and bring data from multiple sources into the pipeline.



2. Choose the Cloud storage category from the left pane and click the Amazon S3 icon to import from Amazon S3. You can also search the required cloud storage services in the search box.
 


NotesNote: If you had already added an Amazon S3 connection earlier, click the Saved connections category from the left pane and proceed to import. To learn more about Saved connections, click here.

3. Authenticate your Amazon S3 account. You will need to authorize DataPrep to access your files when you do this for the first time.

4. Provide necessary details in the
Connection name, Access key, and Secret key fields. 

5. Click the Authenticate Amazon S3 button to authenticate your account with your credentials.




Notes
Note: The connection configuration will be saved for accessing data in Amazon S3 in the future. Credentials are securely encrypted and stored.

6. If you have created a connection already, you can view the existing connection tile. Simply click the connection tile and start importing data. 



NotesClick the Add new link to add a new Amazon S3 account. You can create as many Amazon S3 connections as required.

7. Choose the required bucket and select the files you want to import. Click the Import button. You can also use the Advanced selection option to import files that match a specific pattern. Click here to know more.




8. If the file is an HTML, XLS, or XLSX file, you can click the Preview option to view a sample of the data, or, enter the password if the file is password-protected, and click Import.



9. Once you have completed importing data, Pipeline builder page opens and you can start applying transforms. You can also right-click the stage and choose the Prepare data option and prepare your data in the DataPrep Studio page. Click here to know more about the transforms.




10. Once you are done creating your data flow and applying necessary transforms in your stages, you can right-click a stage and add a destination to complete your data flow.

NotesNote:  After adding a destination to the pipeline, you can try executing your pipeline using a manual run at first. Once you make sure manual run works, you can then set up schedule to automate the pipeline. Learn about the different types of runs here.

Advanced selection

To import files using Advanced selection,

1. Click the advanced selection link.


Advanced selection helps you perform dynamic file selection based on regex. This can be used for getting new or incremental data from your Amazon S3 bucket. The newly added or modified file that matches the file pattern after the previous sync will be taken from your S3 bucket. Click here to know more about incremental fetch.

Info
Important: Advanced selection is used not only for incremental fetch. You can also use this option for bulk import of files based on the file pattern. 

 

2. Provide the following details:

  • Bucket name : The bucket name you want to import data from.

  • Folder path : The folder path where you want to search for files. Eg. 2023/ 
    If the files are stored in the bucket without any folder, you can leave this field empty.

    Alert
    The "Folder Path" is a directory path field and does not support regex patterns.

    InfoInfo: Folder path is case-sensitive.

  • File pattern : The pattern used to match the file names in the bucket. This supports regex type matching. You can also use the pattern, ".*" to match any file in the path specified.

InfoInfo: File pattern is case-sensitive.
Notes
Note: The file pattern match is a simple regex type match. For example, to fetch files with file names such as Sales_2022.csv , Sales_2023.csv , Sales_2024.csv , you can input the pattern Sales_.* 

Similarly to fetch files such as PublicData1.csv , PublicData2.csv , PublicData3.csv , use Public.*

If you want to import a single file, then specify the pattern using the exact file name.
Eg: leads_jan_2022.*
  • Include subfolders : You can also select the Include subfolders checkbox if you want to include subfolders while searching for a file.

  • Parse file as : Choose the required extension to parse the file. If your file format is not a commonly used one, you can use this option to parse the file into one of the following formats before importing the data into a readable format. The available formats are CSV, TSV, JSON, XML, and TXT.

  • Merge files and import - This will merge all the files that match the pattern specified and import them as a single dataset.

    Idea
    You can use this option to merge files together during the import itself, without having to perform unions post import.
    InfoInfo: This option can merge a maximum of only 5 files at a time.
    NotesNote: If this checkbox is unchecked then, only 1 file will be fetched at a time.

    Eg. If your S3 account has 10 files, the first 5 will be merged into one dataset and imported. During the next reload, the remaining 5 files will be merged and imported.

    Similarly, if your S3 account has 8 files, the first 5 will be merged and fetched first, followed by the next 3. 


3. Click the Import button.



NotesNote: We support only CSV, TSV, JSON, XML, and TXT file formats for incremental fetch from cloud storage.

 


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