Apache Spark and TensorFlow on Centos Stream 9 with finance-related Python packages
Apps4Rent LLC
Apache Spark and TensorFlow on Centos Stream 9 with finance-related Python packages
Apps4Rent LLC
Apache Spark and TensorFlow on Centos Stream 9 with finance-related Python packages
Apps4Rent LLC
Apache Spark, TensorFlow and finance-related Python packages on Centos Stream 9 are open source tools
This product includes Apache Spark, TensorFlow along with the open-source finance libraries. Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. Apache Spark is built on an advanced distributed SQL engine for large-scale data
Key features of Apache Spark:
- Apache spark can be used to perform batch processing. Batch/streaming data.
- SQL analytics: Execute fast, distributed ANSI SQL queries for dashboarding and ad-hoc reporting. Runs faster than most data warehouses.
- Machine learning
TensorFlow is an open source platform that lets you create production-grade machine learning models with pre-trained models or your own custom ones.
Features of Tensorflow:
- Multiple APIs: Offers different APIs like Keras and eager execution for ease of use and flexibility.
- End-to-end platform: Covers the entire machine learning workflow, from data preprocessing and model training to deployment and serving.
- Powerful ecosystem: Has a large and active community, extensive documentation, and numerous libraries for specific tasks.
To check the installation of the Apache Spark perform the steps below:
- 1. Update the VM with: sudo yum update. After updating, run sudo su and then cd /root.
- 2. Edit the bashrc configuration file to add Apache Spark installation directory to the system path as below: Run, sudo nano ~/.bashrc Add the code below at the end of the file, save and exit the file: export SPARK_HOME=/opt/spark export PATH=$PATH:$SPARK_HOME/bin:$SPARK_HOME/sbin Save the changes to take effect. Now run, source ~/.bashrc 3. Run, sudo systemctl start httpd 4. Run, sudo firewall-cmd --reload 5. Start the standalone master server by running: start-master.sh 6. To view the Spark Web user interface, open a web browser and enter the public IP address of your instance on port 8080 i.e.: http://your_public_ip_adress:8080/
- 1. sudo su
- 2. cd /root
- 3. Now, run the mentioned command to activate the Python environment: source my-env/bin/activate
- 4. Run the below commands at a time to check the version of TensorFlow and other finance libraries installed: i) pip show tensorflow ii) pip show pyfinance iii) pip show pyspark iv) pip show pyfolio v) pip show pandas-datareader
- 5. To deactivate the environment, run: deactivate
To check the installation of the TensorFlow and finance libraries installed, perform the steps below:
Disclaimer: Apps4Rent does not offer commercial licenses of any of the products mentioned above. The products come with open-source licenses.
Default ports:
- SSH: 22
- HTTP: 80
- HTTPS: 443
- Apache Spark: 8080