LoginEmbeddedEnterpriseContact us
Search…
Welcome to TileDB Cloud!
Tutorials
Start Here!
Console Walkthrough
Serverless Compute 101
Task Graphs 101
Use Cases
Concepts
Universal Data Management
Serverless Compute
Console and API
TileDB Cloud Internals
Pricing and Billing
Marketplace
How To
Sign Up / Sign In
Account
Arrays
Notebooks
UDFs
Organizations
View Tasks
API Reference
Installation
Array Access
Serverless SQL
Serverless UDFs
Serverless Array UDFs
Task Graphs
Utilities
More Help
Forum
Slack
Feature Request
Contact us
Powered By GitBook
Serverless Compute 101
In this tutorial, you will learn:
  1. 1.
    How to access (slice) a public array
  2. 2.
    How to perform a SQL query on a public array.
  3. 3.
    How to perform serverless UDFs on a public array.
We will use public TileDB Cloud array TileDB-Inc/nyc_tlc_yellow_trip_data_2019, which stores the data from the NYC yellow taxi dataset for the year of 2019. The original data is in CSV format with collective size ~7GB, which is converted into a TileDB 1D sparse array with the size being compressed down to ~1GB. The selected sparse dimension is tpep_pickup_datetime, which means that the array supports very fast range slicing on that column of the dataset.

Running on TileDB Cloud

You can preview this tutorial as TileDB Cloud notebook (no login is needed). You can also easily launch it within the TileDB Cloud UI console, but you will need to sign up / login to do so.

Running on your own client

You can run all the commands of this notebook in your own client. The only changes required are:
  1. 1.
    ​Install the TileDB Cloud client
  2. 2.
    ​Log in using the TileDB Cloud client before running any notebook command
Tutorials - Previous
Console Walkthrough
Next - Tutorials
Task Graphs 101
Last modified 11mo ago
Export as PDF
Copy link
Contents
Running on TileDB Cloud
Running on your own client