在 AWS Glue 中使用 CSV 格式

在此範例中，使用 create_dynamic_frame.from_options 方法。

# Example: Read CSV from S3
# For show, we handle a CSV with a header row.  Set the withHeader option.
# Consider whether optimizePerformance is right for your workflow.

from pyspark.context import SparkContext
from awsglue.context import GlueContext

sc = SparkContext.getOrCreate()
glueContext = GlueContext(sc)
spark = glueContext.spark_session

dynamicFrame = glueContext.create_dynamic_frame.from_options(
    connection_type="s3",
    connection_options={"paths": ["s3://s3path"]},
    format="csv",
    format_options={
        "withHeader": True,
        # "optimizePerformance": True,
    },
)

您也可以在指令碼中使用 DataFrames (pyspark.sql.DataFrame)。

dataFrame = spark.read\
    .format("csv")\
    .option("header", "true")\
    .load("s3://s3path")

在此範例中，使用 getSourceWithFormat 操作。

// Example: Read CSV from S3
// For show, we handle a CSV with a header row.  Set the withHeader option.
// Consider whether optimizePerformance is right for your workflow.

import com.amazonaws.services.glue.util.JsonOptions
import com.amazonaws.services.glue.{DynamicFrame, GlueContext}
import org.apache.spark.SparkContext

object GlueApp {
  def main(sysArgs: Array[String]): Unit = {
    val spark: SparkContext = new SparkContext()
    val glueContext: GlueContext = new GlueContext(spark)
    
    val dynamicFrame = glueContext.getSourceWithFormat(
      formatOptions=JsonOptions("""{"withHeader": true}"""),
      connectionType="s3",
      format="csv",
      options=JsonOptions("""{"paths": ["s3://s3path"], "recurse": true}""")
    ).getDynamicFrame()
  }
}

您也可以在指令碼中使用 DataFrames (org.apache.spark.sql.DataFrame)。

val dataFrame = spark.read
  .option("header","true")
  .format("csv")
  .load("s3://s3path“)
			

在此範例中，使用 write_dynamic_frame.from_options 方法。

# Example: Write CSV to S3
# For show, customize how we write string type values.  Set quoteChar to -1 so our values are not quoted.

from pyspark.context import SparkContext
from awsglue.context import GlueContext

sc = SparkContext.getOrCreate()
glueContext = GlueContext(sc)

glueContext.write_dynamic_frame.from_options(
    frame=dynamicFrame,
    connection_type="s3",
    connection_options={"path": "s3://s3path"},
    format="csv",
    format_options={
        "quoteChar": -1,
    },
)

您也可以在指令碼中使用 DataFrames (pyspark.sql.DataFrame)。

dataFrame.write\
    .format("csv")\
    .option("quote", None)\
    .mode("append")\
    .save("s3://s3path")
                    

在此範例中，使用 getSinkWithFormat 方法。

// Example: Write CSV to S3
// For show, customize how we write string type values. Set quoteChar to -1 so our values are not quoted.

import com.amazonaws.services.glue.util.JsonOptions
import com.amazonaws.services.glue.{DynamicFrame, GlueContext}
import org.apache.spark.SparkContext

object GlueApp {
  def main(sysArgs: Array[String]): Unit = {
    val spark: SparkContext = new SparkContext()
    val glueContext: GlueContext = new GlueContext(spark)
    
    glueContext.getSinkWithFormat(
        connectionType="s3",
        options=JsonOptions("""{"path": "s3://s3path"}"""),
        format="csv"
    ).writeDynamicFrame(dynamicFrame)
  }
}

您也可以在指令碼中使用 DataFrames (org.apache.spark.sql.DataFrame)。

dataFrame.write
    .format("csv")
    .option("quote", null)
    .mode("Append")
    .save("s3://s3path")