TileDB with Dask Array

TileDB integrates very well with dask.array. We demonstrate with an example below where attribute attr stores an int32 value per cell:

Python

import dask
import dask.array as da

array = da.from_tiledb('s3://my-bucket/my-dense-array',
                        attribute='attr',
                        storage_options={'vfs.s3.aws_access_key_id': 'mykeyid',
                                         'vfs.s3.aws_secret_access_key': 'mysecret'})
print(array.mean().compute())

You can add any TileDB configuration parameter in storage_options. Moreover, storage_options accepts an additional key option, where you can pass an encryption key if your array is encrypted (see Encryption).

You can also set array chunking similar to Dask's chunking. For example, you can do the following:

Python

import dask
import dask.array as da

array = da.from_tiledb('s3://my-bucket/my-dense-array',
                        attribute='attr',
                        chunks=10, # or chunks=(10,) 
                        storage_options={'vfs.s3.aws_access_key_id': 'mykeyid',
                                         'vfs.s3.aws_secret_access_key': 'mysecret'})
print(array.mean().compute())

You can also write a Dask array into TileDB as follows:

Python

import tiledb
import numpy as np
import dask, dask.array as da

array = da.random.random((25,25))

array.to_tiledb("s3://my-bucket/my-uri", storage_options={'vfs.s3.aws_access_key_id': 'mykeyid',
                                      'vfs.s3.aws_secret_access_key': 'mysecret'})

Note that the TileDB array does not need to exist. The above function call will create it if it does not by inferring the schema from the Dask array. To write to an existing array, you should open the array for writing as follows:

Python

import numpy as np
import dask, dask.array as da

array = da.random.random((25,25))

with tiledb.open(s3://my-bucket/my-uri, 'w') as A:
    array.to_tiledb(A)