Estudos e projetos feitos com PySpark.

Overview

PySpark (Spark com Python)

PySpark é uma biblioteca Spark escrita em Python, e seu objetivo é permitir a análise interativa dos dados em um ambiente distribuído. Seu uso é extremamente importante quando o assunto é grande volume de dados, BigData, por conta do seu processamento eficiente de grandes conjuntos de dados.

Documentação

Data

Os dados para esse tutorial foram obtidos no Kaggle, a base é pequena, então teoricamente utilizar o pyspark nesse caso seria "matar uma mosca com um canhão", mas como o objetivo é explorar as principais funções, esse dataset vai nos atender bem.

Para fazer download desse conjunto de dados você precisa ter uma conta no kaggle.

Tópicos

Vamos explorar as principais funções:

  • Count
  • Describe
  • Select
  • OrderBy
  • WithColumnRenamed
  • WithColumn
  • When
  • Drop
  • Filter
  • Where
  • GroupBy

Requisitos

Você precisará de Python 3 e pip. É altamente recomendado utilizar ambientes virtuais com o virtualenv ou com o conda e o arquivo requirements.txt para instalar os pacotes dependências do projeto:

Conda

$ conda create --name nameenv python
$ conda activate nameenv
$ pip install -r requirements.txt

Virtualenv

$ pip3 install virtualenv
$ virtualenv venv -p python3
$ source venv/bin/activate
$ pip install -r requirements.txt

Observação

Para executar o PySpark, você também precisa que o Java seja instalado.

Owner
Karinne Cristina
Data Scientist | Data Analyst
Karinne Cristina
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