Load from the AWS S3

If you store your data in AWS S3, TigerGraph Cloud provides seamless integration for data ingestion. You can directly load data from your S3 buckets into your graph databases, eliminating the need for manual data transfers. This simplifies the process of importing large datasets and enables you to leverage the scalability and durability of AWS S3 for your graph analysis.

1) Select Source

Once you’ve selected AWS S3, you will be asked to configure the AWS S3 data source.
  1. Click on Screenshot 2024 04 17 at 9.36.58 PM to add a new AWS S3 data source.

    Screenshot 2024 04 17 at 9.36.27 PM

  2. You will need to provide your S3 AWS access key id and S3 AWS secret access key.

    Screenshot 2024 04 17 at 9.37.32 PM

  3. Once you have those configured, you can add one or multiple S3 URI within the same S3 bucket.

  4. Click Next to process the file(s).

    The current data loading tool only supports CSV files. Other formats will be available in later releases.

2) Configure File

This step lets you configure the source file details.
  1. The data loading tool will automatically detect the .csv separators and line breaks. The parser automatically splits each line into a series of tokens.

    Screenshot 2024 04 17 at 5.53.45 PM

    If the parsing is not correct, click on the Screenshot 2024 04 17 at 5.54.17 PM button to configure a different option for the delimiter, such as eol, or quote and header.

    Screenshot 2024 04 17 at 5.54.50 PM

    The enclosing character is used to mark the boundaries of a token, overriding the delimiter character.

    For example, if your delimiter is a comma, but you have commas in some strings, then you can define single or double quotes as the enclosing character to mark the endpoints of your string tokens.

    It is not necessary for every token to have enclosing characters. The parser uses enclosing characters when it encounters them.

    You can edit the header line of the parsing result to give each column a more intuitive name, since you will be referring to these names when loading data to the graph. The header name is ignored during data loading.

  2. Once you are satisfied with the file settings, click Next to proceed.

3) Configure Map

If you are loading data into a brand new graph, you will be prompted to let our engine generate a schema and mapping for you. Or you can start from scratch. For more details of schema design please refer to Schema Designer.
  1. Select Generate the schema only or Generate the schema and data mapping.

    Screenshot 2024 04 17 at 5.55.35 PM

    TigerGraph Cloud 4.0 is still in beta release and the schema generation feature is still a preview feature. The correctness and efficiency of the resulting graph schema and mapping could vary.

  2. In the Source column, you can choose the specific column from the data source that you want to map with the attribute.

    Screenshot 2024 04 17 at 5.56.15 PM
  3. Use the + button to create a new attribute of the target vertex or edge.

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  4. The Map all to target button aligns existing attribute names with the corresponding data source headers to establish mappings and also introduces new attributes based on unmatched data source headers.

    Screenshot 2024 04 17 at 5.57.52 PM
  5. Click Next to proceed.

4) Confirm

This step will let you confirm the changes made to the schema and the data mapping you created to load the data.
  1. Simply review the Schema to be change and Data to be loaded lists.

    Screenshot 2024 04 17 at 5.58.36 PM

    Please be aware that some schema changes will result in unintentional deletion of the data. Please carefully review the warning message before confirming the loading.

  2. Click on the Confirm button to run the loading jobs and monitor their Status.

    Screenshot 2024 04 17 at 5.59.16 PM

Next Steps

Next, learn how to use the Schema Designer in TigerGraph Cloud 4.0.

Or return to the Overview page for a different topic.