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spark_structured_streaming_demo's Introduction

Spark Log Analytics

1. Overview

A Log Analytics demo based on Spark Structured Streaming + Kafka

2. Get started

2.1 Setup Conda env

conda create -y -n yz_spark_kafka_demo python=3.6
source activate spark_kafka_demo
pip install kafka-python
pip install pyspark
pip install pandas

2.2 Run Kafka in Docker

docker run -p 2181:2181 -p 9092:9092 --env ADVERTISED_HOST=localhost --env ADVERTISED_PORT=9092 spotify/kafka

2.3 Run Kafka producer

Open a terminal and run the following commands (please unarchive apache-access-log.txt.gz first)

source activate yz_spark_kafka_demo
gunzip apache-access-log.txt.gz
python step1-kafka-producer.py -i ./apache-access-log.txt --host 127.0.0.1:9092 --topic logs

2.4 Streaming processor

Open a new terminal and run the following commands

source activate yz_spark_kafka_demo
python step2-streaming-processor.py --host 127.0.0.1:9092 --topic logs

2.5 QA

Open a new terminal and run the following commands

source activate yz_spark_kafka_demo
python step3-QA.py --path ./data

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