ArangoDB v3.13 is under development and not released yet. This documentation is not final and potentially incomplete.
Start the import
Once the data files are provided and the graph is designed, you can start the import
Before starting the actual import, make sure that:
- You have selected a database for import or created a new one;
- You have provided a valid name for your graph;
- You have created at least one node;
- You have created at least one edge;
- You have uploaded at least one file;
- Every file is related to at least one node or edge;
- Every node and edge is linked to a file;
- Every node and edge has a unique label;
- Every node has a primary identifier selected;
- Every edge has an origin and destination file header selected.
To continue with the import, click the Save and start import button. The data importer provides an overview showing results with the collections that have been created with the data provided in the files.
To access your newly created graph in the ArangoDB web interface, click the See your new graph button.
File validation
Once the import has started, the files that you have provided are being validated. If the validation process detects parsing errors in any of the files, the import is temporarily paused and the validation errors are shown. You can get a full report by clicking the See full report button.
At this point, you can:
- Continue with the import without addressing the errors. The CSV files will still be included in the migration. However, the invalid rows are skipped and excluded from the migration.
- Revisit the problematic file(s), resolve the issues, and then re-upload the file(s) again.
Validation errors and their meanings
Invalid Quotation Mark
This error indicates issues with quotation marks in the CSV data. It can occur due to improper use of quotes.
Missing Quotation Marks
This error occurs when quotation marks are missing or improperly placed in the CSV data, potentially affecting data enclosure.
Insufficient Data Fields
This error occurs when a CSV row has fewer fields than expected. It may indicate missing or improperly formatted data.
Excessive Data Fields
This error occurs when a CSV row has more fields than expected, possibly due to extra data or formatting issues.
Unidentifiable Field Separator
This error suggests that the parser could not identify the field separator character in the CSV data.