Course covers big data fundamentals, processes, technologies, platform ecosystem, and management for practical application development.
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Updated
Apr 7, 2024 - Jupyter Notebook
Course covers big data fundamentals, processes, technologies, platform ecosystem, and management for practical application development.
A lightweight helper utility which allows developers to do interactive pipeline development by having a unified source code for both DLT run and Non-DLT interactive notebook run.
This repository contains an Apache Flink application for real-time sales analytics built using Docker Compose to orchestrate the necessary infrastructure components, including Apache Flink, Elasticsearch, and Postgres
This code creates a Kinesis Firehose in AWS to send CloudWatch log data to S3.
Eskimo is a state of the art Big Data Infrastructure and Management Web Console to build, manage and operate Big Data 2.0 Analytics clusters on Kubernetes. This is the git repository of Eskimo Community Edition.
Flink SQL 实战 -中文博客专栏
Yet Another SPark Framework
big data processing and machine learning platform,just like useing sql
R for Big Data (Chinese Version)
GCP_Data_Enginner
🛠️ Python library to import OCR data in various formats into the canonical JSON format defined by the Impresso project.
Data modeling with Cassandra, building Data Warehouse using Redshift and creation of Data Lake using Spark and Airflow
A curated selection of tools, libraries and services that help tame your dataflow to productively build ambitious, data driven & reactive applications on a streaming lakehouse
Here I demonstrate the performance difference between the Poisson and the classic bootstrap by estimating the confidence interval for the difference of CTRs of the two user groups
Reservoir Sampling for Group-By Queries in Flink Platform. Answering effectively Single Aggregate.
Implementation of algorithms for big data using python, numpy, pandas.
Github Repository for a versatile usable Big Data infrastructure (AVUBDI)
A pipeline that consumes twitter data to extract meaningful insights about a variety of topics using the following technologies: twitter API, Kafka, MongoDB, and Tableau.
Introduction to Spark Batch processing.
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