小编Jer*_*emy的帖子

我正在查询information_schema.columnsPostgreSQL数据库中的表.使用表名,结果集将查找所有列名,类型以及它是否可为空(主键除外,'id').这是使用的查询:

SELECT column_name, is_nullable,data_type FROM information_schema.columns
WHERE lower(table_name) = lower('TABLE1') AND column_name != 'id'
ORDER BY ordinal_position;

我为每个结果都有一个字符串数组,我试图使用ResultSet方法getArray(String columnLabel)来避免循环结果.我想将返回的数组存储在字符串数组中,但是会出现类型不匹配错误

Type mismatch: cannot convert from Array to String[]

有没有办法将SQL Array对象转换或类型转换为String []？

相关守则:

String[] columnName, type, nullable;

//Get Field Names, Type, & Nullability 
String query = "SELECT column_name, is_nullable,data_type FROM information_schema.columns "
        + "WHERE lower(table_name) = lower('"+tableName+"') AND column_name != 'id' "
        + "ORDER BY ordinal_position";

try{
    ResultSet rs = Query.executeQueryWithRS(c, query);
    columnName = rs.getArray(rs.getArray("column_name"));
    type = rs.getArray("data_type"); …

我有一些spark scala代码在spark-shell中没有问题.

这个问题的核心在于这几条线.我想在数据框中添加一行:

object SparkPipeline {

  def main(args: Array[String]) {
    val spark = (SparkSession
        .builder()
        .appName("SparkPipeline")
        .getOrCreate()
        )

    df = (spark
        .read
        .format("com.databricks.spark.avro")
        .load(DATA_PATH)
        )

    case class DataRow(field1: String, field2: String)
    val row_df = Seq(DataRow("FOO", "BAR")).toDF()  // THIS FAILS
    val df_augmented = df.union(row_df)
    //
    // Additional code here
    //
  }
}

但是,当我使用sbt将其打包为jar时,sbt失败并出现以下错误:

value toDF is not a member of Seq[DataRow]

我试着按照这个问题来做:

val spark = (SparkSession
    .builder()
    .appName("TrainSimpleRF")
    .getOrCreate()
    )

val sc = spark.sparkContext
val sqlContext= new org.apache.spark.sql.SQLContext(sc)
import …