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OmniSci EE

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Description

OmniSci (formerly MapD) is the pioneer in GPU-accelerated analytics, redefining speed and scale in big data querying and visualization. The OmniSci platform is used to find insights in data beyond the limits of mainstream analytics tools.

Publisher

OmniSci

Latest Tag

cuda10-5.1.1

Modified

September 24, 2020

Compressed Size

1.76 GB

Multinode Support

No

Multi-Arch Support

No

What is OmniSci?


OmniSci is the world's fastest SQL engine which helps you find hidden insights beyond the reach of mainstream analytics, by letting you query and visually explore large datasets at extreme speed. OmniSci can query up to billions of rows in milliseconds, and is capable of unprecedented ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data while harnessing the massive parallel computing power of CPUs and GPUs alike.

OmniSci platform seamlessly integrates with existing CPU-based legacy analytics systems, becoming the bridge needed to generate the optimal speed and scale for Big Data processing. OmniSci provides analysts and data scientists with no-lag data processing (no need to do any pre-aggregation or downsampling).

Break down silos with the only open platform that unites analytics, data science and location intelligence workflows. Leverage native SQL, interactive visual analytics, extensive PyData stack integrations, and a powerful machine learning framework. Interactively query, visualize, and power data science workflows over billions of records with OmniSci

Note: Add --gpus=all to docker run command in case of error ./bin/initdb: error while loading shared libraries: libcuda.so.1: cannot open shared object file: No such file or directory

EULA and User Documentation


  1. EULA
  2. Container Installation Guide
  3. OmniSci Release Notes
  4. Immerse User Guide

Running OmniSci


Sample nvidia-docker run:

docker run --runtime=nvidia \
-v $HOME/omnisci-docker-storage:/omnisci-storage \
-p 6273-6280:6273-6280 \
omnisci/omnisci-os-cuda

Go to https://www.omnisci.com/platform/downloads/enterprise/ and fill out the form to get a trial license key. The key will be emailed to you after you fill out the form.

Use the browser to open OmniSci Immerse and enter the license key by connecting to:

http://:6273

Importing a Sample Dataset


OmniSci ships with two sample datasets of airline flight information collected in 2008, and one dataset of New York City census information collected in 2015. To install the sample data, run the following command.

docker exec -it  ./insert_sample_data

Where is the container in which OmniSci is running When prompted, choose whether to insert dataset 1 (7,000,000 rows), dataset 2 (10,000 rows), or dataset 3 (683,000 rows). The examples below use dataset 2.

Enter dataset number to download, or 'q' to quit:

#  Dataset                   Rows       Table Name                     File Name
1. Flights (2008)            7M        flights_2008_7M             flights_2008_7M.tar.gz
2. Flights (2008)            10k       flights_2008_10k            flights_2008_10k.tar.gz
3. NYC Tree Census (2015)    683k      nyc_trees_2015_683k         nyc_trees_2015_683k.tar.gz

Connecting to the OmniSci Command Line (OmniSQL)


Connect to OmniSci Core by entering the following command (default password is HyperInteractive):

docker exec -it  /omnisci/bin/omnisql
password: ••••••••••••••••

Enter a SQL query such as the following:

omnisql> SELECT origin_city AS "Origin", dest_city AS "Destination", AVG(airtime) AS
"Average Airtime" FROM flights_2008_10k WHERE distance < 175 GROUP BY origin_city,
dest_city;

Contact OmniSci


If you have general enquiries or are interested in upgrading from the Community Edition to the Enterprise Edition please email sales@omnisci.com. You can also visit the OmniSci community forum to learn more.