> ## Documentation Index
> Fetch the complete documentation index at: https://clickhouse.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

> Integre o ClickHouse ao Amazon Glue

# Integrando o Amazon Glue ao ClickHouse e ao Spark

export const ClickHouseSupportedBadge = () => {
  return <div className="ClickHouseSupportedBadge">
            <div className="ClickHouseSupportedIcon">
                <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
                    <path d="M1.30762 1.39073C1.30762 1.3103 1.37465 1.22986 1.46849 1.22986H2.64824C2.72868 1.22986 2.80912 1.29689 2.80912 1.39073V14.4886C2.80912 14.5691 2.74209 14.6495 2.64824 14.6495H1.46849C1.38805 14.6495 1.30762 14.5825 1.30762 14.4886V1.39073Z" fill="currentColor" />
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                </svg>
            </div>
            Suportado pelo ClickHouse
        </div>;
};

export const Image = ({img, alt, size = "lg"}) => {
  const normalizedSize = ["sm", "md", "lg"].includes(size) ? size : "lg";
  return <div className={`ch-image-${normalizedSize}`}>
      <Frame>
        <img src={img} alt={alt} />
      </Frame>
    </div>;
};

<ClickHouseSupportedBadge />

[Amazon Glue](https://aws.amazon.com/glue/) é um serviço de integração de dados totalmente gerenciado e sem servidor fornecido pela Amazon Web Services (AWS). Ele simplifica o processo de descoberta, preparação e transformação de dados para análise, aprendizado de máquina e desenvolvimento de aplicações.

<div id="installation">
  ## Instalação
</div>

Para integrar seu código do Glue ao ClickHouse, você pode usar nosso Spark connector oficial no Glue de uma das seguintes formas:

* Instalar o ClickHouse Glue Connector pelo AWS Marketplace (recomendado).
* Adicionar manualmente os JARs do Spark Connector ao seu job do Glue.

<Tabs>
  <Tab title="AWS Marketplace">
    1. <h3 id="subscribe-to-the-connector">Assinar o connector</h3>
       Para acessar o connector na sua conta, assine o ClickHouse AWS Glue Connector no AWS Marketplace.

    2. <h3 id="grant-required-permissions">Conceder as permissões necessárias</h3>
       Certifique-se de que a IAM role do seu job do Glue tenha as permissões necessárias, conforme descrito no [guia](https://docs.aws.amazon.com/glue/latest/dg/getting-started-min-privs-job.html#getting-started-min-privs-connectors) de privilégios mínimos.

    3. <h3 id="activate-the-connector">Ativar o connector e criar uma conexão</h3>
       Você pode ativar o connector e criar uma conexão diretamente clicando [neste link](https://console.aws.amazon.com/gluestudio/home#/connector/add-connection?connectorName="ClickHouse%20AWS%20Glue%20Connector"\&connectorType="Spark"\&connectorUrl=https://709825985650.dkr.ecr.us-east-1.amazonaws.com/clickhouse/clickhouse-glue:1.0.0\&connectorClassName="com.clickhouse.spark.ClickHouseCatalog"), que abre a página de criação de conexão do Glue com os principais campos já preenchidos. Dê um nome à conexão e clique em Create (não é necessário informar os detalhes de conexão do ClickHouse nesta etapa).

    4. <h3 id="use-in-glue-job">Usar no job do Glue</h3>
       No seu job do Glue, selecione a aba `Job details` e expanda a seção `Advanced properties`. Na seção `Connections`, selecione a conexão que você acabou de criar. O connector injeta automaticamente os JARs necessários no ambiente de execução do job.

    <Image img="https://mintcdn.com/private-7c7dfe99/k4wNHsd_gyvah7Fr/images/integrations/data-ingestion/aws-glue/notebook-connections-config.webp?fit=max&auto=format&n=k4wNHsd_gyvah7Fr&q=85&s=6d6ebaacb208344b3c12e9d74176cd0d" size="md" alt="Configuração de conexões do notebook do Glue" force="true" width="877" height="742" data-path="images/integrations/data-ingestion/aws-glue/notebook-connections-config.webp" />

    <Note>
      Os JARs usados no connector do Glue são compilados para `Spark 3.3`, `Scala 2` e `Python 3`. Certifique-se de selecionar essas versões ao configurar seu job do Glue.
    </Note>
  </Tab>

  <Tab title="Instalação manual">
    Para adicionar manualmente os JARs necessários, siga estas etapas:

    1. Faça upload dos seguintes JARs para um bucket do S3: `clickhouse-jdbc-0.6.X-all.jar` e `clickhouse-spark-runtime-3.X_2.X-0.8.X.jar`.
    2. Certifique-se de que o job do Glue tenha acesso a esse bucket.
    3. Na aba `Job details`, role para baixo, expanda o menu suspenso `Advanced properties` e preencha o caminho dos JARs em `Dependent JARs path`:

    <Image img="https://mintcdn.com/private-7c7dfe99/k4wNHsd_gyvah7Fr/images/integrations/data-ingestion/aws-glue/dependent_jars_path_option.webp?fit=max&auto=format&n=k4wNHsd_gyvah7Fr&q=85&s=74f65422ba8e4c0d59ce3ada60dc2045" size="md" alt="Opções de caminho de JAR do notebook do Glue" force="true" width="954" height="753" data-path="images/integrations/data-ingestion/aws-glue/dependent_jars_path_option.webp" />
  </Tab>
</Tabs>

<div id="example">
  ## Exemplos
</div>

<Tabs>
  <Tab title="Scala">
    ```java theme={null}
    import com.amazonaws.services.glue.GlueContext
    import com.amazonaws.services.glue.util.GlueArgParser
    import com.amazonaws.services.glue.util.Job
    import com.clickhouseScala.Native.NativeSparkRead.spark
    import org.apache.spark.sql.SparkSession

    import scala.collection.JavaConverters._
    import org.apache.spark.sql.types._
    import org.apache.spark.sql.functions._

    object ClickHouseGlueExample {
      def main(sysArgs: Array[String]) {
        val args = GlueArgParser.getResolvedOptions(sysArgs, Seq("JOB_NAME").toArray)

        val sparkSession: SparkSession = SparkSession.builder
          .config("spark.sql.catalog.clickhouse", "com.clickhouse.spark.ClickHouseCatalog")
          .config("spark.sql.catalog.clickhouse.host", "<your-clickhouse-host>")
          .config("spark.sql.catalog.clickhouse.protocol", "https")
          .config("spark.sql.catalog.clickhouse.http_port", "<your-clickhouse-port>")
          .config("spark.sql.catalog.clickhouse.user", "default")
          .config("spark.sql.catalog.clickhouse.password", "<your-password>")
          .config("spark.sql.catalog.clickhouse.database", "default")
          // for ClickHouse cloud
          .config("spark.sql.catalog.clickhouse.option.ssl", "true")
          .config("spark.sql.catalog.clickhouse.option.ssl_mode", "NONE")
          .getOrCreate

        val glueContext = new GlueContext(sparkSession.sparkContext)
        Job.init(args("JOB_NAME"), glueContext, args.asJava)
        import sparkSession.implicits._

        val url = "s3://{path_to_cell_tower_data}/cell_towers.csv.gz"

        val schema = StructType(Seq(
          StructField("radio", StringType, nullable = false),
          StructField("mcc", IntegerType, nullable = false),
          StructField("net", IntegerType, nullable = false),
          StructField("area", IntegerType, nullable = false),
          StructField("cell", LongType, nullable = false),
          StructField("unit", IntegerType, nullable = false),
          StructField("lon", DoubleType, nullable = false),
          StructField("lat", DoubleType, nullable = false),
          StructField("range", IntegerType, nullable = false),
          StructField("samples", IntegerType, nullable = false),
          StructField("changeable", IntegerType, nullable = false),
          StructField("created", TimestampType, nullable = false),
          StructField("updated", TimestampType, nullable = false),
          StructField("averageSignal", IntegerType, nullable = false)
        ))

        val df = sparkSession.read
          .option("header", "true")
          .schema(schema)
          .csv(url)

        // Write to ClickHouse
        df.writeTo("clickhouse.default.cell_towers").append()

        // Read from ClickHouse
        val dfRead = spark.sql("select * from clickhouse.default.cell_towers")
        Job.commit()
      }
    }
    ```
  </Tab>

  <Tab title="Python">
    ```python theme={null}
    import sys
    from awsglue.transforms import *
    from awsglue.utils import getResolvedOptions
    from pyspark.context import SparkContext
    from awsglue.context import GlueContext
    from awsglue.job import Job
    from pyspark.sql import Row

    ## @params: [JOB_NAME]
    args = getResolvedOptions(sys.argv, ['JOB_NAME'])

    sc = SparkContext()
    glueContext = GlueContext(sc)
    logger = glueContext.get_logger()
    spark = glueContext.spark_session
    job = Job(glueContext)
    job.init(args['JOB_NAME'], args)

    spark.conf.set("spark.sql.catalog.clickhouse", "com.clickhouse.spark.ClickHouseCatalog")
    spark.conf.set("spark.sql.catalog.clickhouse.host", "<your-clickhouse-host>")
    spark.conf.set("spark.sql.catalog.clickhouse.protocol", "https")
    spark.conf.set("spark.sql.catalog.clickhouse.http_port", "<your-clickhouse-port>")
    spark.conf.set("spark.sql.catalog.clickhouse.user", "default")
    spark.conf.set("spark.sql.catalog.clickhouse.password", "<your-password>")
    spark.conf.set("spark.sql.catalog.clickhouse.database", "default")
    spark.conf.set("spark.clickhouse.write.format", "json")
    spark.conf.set("spark.clickhouse.read.format", "arrow")
    # for ClickHouse cloud
    spark.conf.set("spark.sql.catalog.clickhouse.option.ssl", "true")
    spark.conf.set("spark.sql.catalog.clickhouse.option.ssl_mode", "NONE")

    # Create DataFrame
    data = [Row(id=11, name="John"), Row(id=12, name="Doe")]
    df = spark.createDataFrame(data)

    # Write DataFrame to ClickHouse
    df.writeTo("clickhouse.default.example_table").append()

    # Read DataFrame from ClickHouse
    df_read = spark.sql("select * from clickhouse.default.example_table")
    logger.info(str(df.take(10)))

    job.commit()
    ```
  </Tab>
</Tabs>