docker-spark-iceberg
Spark environment
A Docker-based environment for running Spark and Iceberg in a quick start scenario.
256 stars
13 watching
128 forks
Language: Jupyter Notebook
last commit: 11 days ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 jupyter-incubator/sparkmagic | An open source library that enables interactive development of applications using remote Spark clusters | 1,328 |
 sequenceiq/docker-spark | A Docker image with Apache Spark pre-installed and configured for easy deployment on YARN clusters. | 765 |
| databricks/spark-xml | A library that parses and queries XML data in Apache Spark | 505 |
| databricks/spark-csv | A library for parsing and querying CSV data with Apache Spark | 1,053 |
 apple/batch-processing-gateway | A tool to simplify running Spark on Kubernetes | 181 |
 svenkreiss/pysparkling | A lightweight Python implementation of Spark's RDD and DStream interfaces for improved performance on small datasets | 262 |
 yannael/kafka-sparkstreaming-cassandra | An environment for experimenting with real-time data processing using Kafka, Spark streaming, and Cassandra | 97 |
| databricks/spark-corenlp | Wraps Stanford CoreNLP annotators as Spark DataFrame functions for natural language processing tasks | 422 |
 indix/sparkplug | A Spark-based package to apply data fixes using rule-based SQL conditions | 28 |
 sparklyr/sparklyr | An R interface to Apache Spark for distributed data analysis and machine learning | 957 |
 apache/spark | An analytics engine designed to handle large-scale data processing and analysis | 39,916 |
| databricks/tensorframes | Enables manipulation of Apache Spark DataFrames using TensorFlow programs | 749 |
 instaclustr/sample-kafkasparkcassandra | An introductory Scala app using Apache Spark Streaming to process data from Kafka and write summaries to Cassandra. | 23 |
 ellerbrock/docker-tutorial | A comprehensive guide to Docker development and deployment | 14 |
 kcrandall/emr_spark_automation | Automates deployment of an AWS EMR cluster and execution of Spark jobs | 8 |