660 Open source projects that are alternatives of or similar to bandar-log

Monitoring tool to measure flow throughput of data sources and processing components that are part of Data Ingestion and ETL pipelines.

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📊 Cube — Open-Source Analytics API for Building Data Apps

A complete example of a big data application using : Kubernetes (kops/aws), Apache Spark SQL/Streaming/MLib, Apache Flink, Scala, Python, Apache Kafka, Apache Hbase, Apache Parquet, Apache Avro, Apache Storm, Twitter Api, MongoDB, NodeJS, Angular, GraphQL

code, labs and lectures for the course

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Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

Web-based SQL editor run in your own private cloud. Supports MySQL, Postgres, SQL Server, Vertica, Crate, ClickHouse, Trino, Presto, SAP HANA, Cassandra, Snowflake, BigQuery, SQLite, and more with ODBC

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Simplified ETL process in Hadoop using Apache Spark. Has complete ETL pipeline for datalake. SparkSession extensions, DataFrame validation, Column extensions, SQL functions, and DataFrame transformations

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OpenRefine is a free, open source power tool for working with messy data and improving it. This repository contains Dockerbuild files for automated builds.

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GAMECHANGER aspires to be the Department’s trusted solution for evidence-based, data-driven decision-making across the universe of DoD requirements

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Structural Bioinformatics Training Workshop & Hackathon 2018

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Linkis helps easily connect to various back-end computation/storage engines(Spark, Python, TiDB...), exposes various interfaces(REST, JDBC, Java ...), with multi-tenancy, high performance, and resource control.

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❄️ 🐳 Awesome tools and libs for AI, Deep Learning, Machine Learning, Computer Vision, Data Science, Data Analytics and Cognitive Computing that are baked in the oven to be Native on Kubernetes and Docker with Python, R, Scala, Java, C#, Go, Julia, C++ etc

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简单的可视化湖州通话数据 假设数据量很大，没法用浏览器直接绘制热力图，把绘制热力图这一步骤放到线下计算分析。使用Apache Spark并行计算数据之后，再使用Apache Spark绘制热力图，然后用leafletjs加载OpenStreetMap图层和热力图图层，以达到良好的交互效果。现在使用Apache Spark实现绘制，可能是Apache Spark不擅长这方面的计算或者是我没有设计好算法，并行计算的速度比不上单机计算。Apache Spark绘制热力图和计算代码在这 https://github.com/yuanzhaokang/ParallelizeHeatmap.git .

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