Easily load data from CSV to test out your DynamoDB table design
Project description
dynamodb-dev-importer
Easily load data from CSV to test out your DynamoDB table design.
When working with DynamoDB, it is common practice to minimise the number of tables used, ideally down to just one.
Techniques such as sparse indexes and GSI overloading allow a lot of flexibility and efficiency.
Designing a good schema that supports your query patterns can be challenging. Often it is nice to try things out with a small amount of data. I personally find it convenient to enter data into a spreadsheet and play around with it there.
This utility eases the process of populating a DynamoDB table from a CSV file, exported from a spreadsheet, that follows a specific format common to DynamoDB modelling patterns.
Install
You can install it with
$ pip3 install ddbimp
You can find the code on Github too.
Run
Assuming table people(pk:S, sk:S)
is provisioned in your default region.
$ ddbimp --table people --skip 1 example.csv
Expected input format
pk | sk | data | ||
---|---|---|---|---|
PERSON-1 | sales-Q1-2019 | Alex | jan: 12012 | feb: 1927 |
Your spreadsheet (and exported CSV) should contain columns for:
- pk
- sk
- data (optional)
- anything after those three can contain arbitrary attributes of form
attribute_name: value
i.e.city: Edinburgh
Example row:
PERSON-1,sales-Q1-2019,Alex,jan: 12012,feb: 1927
Will yield an item like this:
{
pk: 'PERSON-1',
sk: 'sales-Q1-2019',
data: 'Alex',
jan: 12012,
feb 1927
}
For a full example CSV, take a look at example.csv.
Key ideas
- Table consists of partition key
pk: S
and sort keysk: S
- their meaning varies depending on the item - A secondary index swaps the sort and partition keys, so the partition key is
sk: S
and sort keypk: S
- A final secondary index uses
sk: S
anddata: S
where data is an arbitrary value you might want to search for, the meaning ofdata
depends on the item it is part of - Group items through a shared partition key, store sub items with a sort key e.g.
- e.g.
pk:PERSON-1, sk:sales-Q1-2019, jan:12012, feb:1927
- e.g.
AWS recently released a preview build of a tool called NoSQL Workbench. It builds on the above ideas. I've tried it out and it seems pretty good, but I am a luddite and am faster working in a spreadsheet right now. I'd certainly recommend giving it a try.
Useful resources
- https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/bp-indexes.html
- https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/workbench.html
- https://www.youtube.com/watch?v=6yqfmXiZTlM
Caveats, TODO
- Uses your default AWS profile
- Region needs to be set
- Make work directly with a Google Sheets via sheets API
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