- Acessar S3: https://s3.console.aws.amazon.com/s3/
- Criar estrutura de data lake : dio-live-datalake
- Criar estrutura de pastas:
- data
- output
- temp
- Acessar EMR: https://console.aws.amazon.com/elasticmapreduce/
- O cluster será criado pelo MrJob e não pelo console
- Infraestrutura como código
- Criar chave SSH
- Acessar Console do EC2: https://console.aws.amazon.com/ec2/ -> Key Pairs -> Create Key Pair
- Download .pem file
- Obter Id e chave secreta AWS para configurar MrJob
- Profile
- My Security Credentials: https://console.aws.amazon.com/iam/home?region={region}#/security_credentials
- Access Keys - Create new access key
- Fazer download - única chance de visualizar
- Ambiente linux
- Criar ambiente virtual python: virtualenv --python=python3.6 venv_diolive
- Acessar com o vs code
- Instalar vscode no Ubuntu
- code .
- Criar algoritmo de análise de palavras
- dio-live-wordcount-test.py
- map-reduce-count : contar
- Instalar boto3: pip install boto3
- Instalar mrjob: pip install mrjob
- Acessar S3
- Upload de arquivo para o bucket
- Ambiente virtual python: source venv_teste/bin/activate
- nano ~/.mrjob.conf
- python3 dio-live-wordcount-test.py -r emr s3://{your_s3_bucket_name}/data/SherlockHolmes.txt --output-dir=s3://{your_s3_bucket_name}/output/logs1 --cloud-tmp-dir=s3://{your_s3_bucket_name}/temp/
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