Objects made from Apex classes defined by the user.An enumeration is a typed list of values.A primitive-to-primitive map, sObject, or collection.A list (or array) of primitives, sObjects, user-defined objects, Apex classescreated objects or collections.A collection that includes the following items:.A sObject, such as an Account, Contact, or M圜ustomObject c, is either general or particular.Integer, Double, Long, Date, Datetime, String, ID, or Boolean are examples of primitives.We use these data types as it is required depending on the condition. Apex in Salesforce assigns a data type to all variables and expressions, such as sObject, primitive, or enum. redshift OPTIONS ( dbtable 'tbl_write', forward_spark_s3_credentials 'true', tempdir 's3n://path/for/temp/data' url 'jdbc:redshift://redshifthost:5439/database?user=username&password=pass' ) AS SELECT * FROM tabletosave - Using IAM Role based authentication instead of keys CREATE TABLE tbl USING com. redshift OPTIONS ( query 'select x, count(*) from table_in_redshift group by x', forward_spark_s3_credentials 'true', tempdir 's3://path/for/temp/data', url 'jdbc:redshift://redshifthost:5439/database?user=username&password=pass', ) - Writing to Redshift - Create a new table in redshift, throws an error if a table with the same name already exists CREATE TABLE tbl_write USING com. redshift OPTIONS ( dbtable 'tbl', forward_spark_s3_credentials 'true', tempdir 's3://path/for/temp/data', url 'jdbc:redshift://redshifthost:5439/database?user=username&password=pass', ) - Load Redshift query results in a Spark dataframe CREATE TABLE tbl USING com. Spark Redshift connector Example Notebook - SQL - Read from Redshift - Read Redshift table using dataframe apis CREATE TABLE tbl USING com. # Spark Redshift connector Example Notebook - SparkR jdbcURL df ) save () # Using IAM Role based authentication instead of keys df. save () // To overwrite data in Redshift table df. load () # Create a new redshift table with the given dataframe data # df = df. option ( "query", "select col1, col2 from tbl group by col3" ) \ load () # Load Redshift query results in a Spark dataframe df = spark. option ( "forward_spark_s3_credentials", "true" ). # Spark Redshift connector Example Notebook - PySpark jdbcURL = "jdbc:redshift://redshifthost:5439/database?user=username&password=pass" tempS3Dir = "s3://path/for/temp/data" # Read Redshift table using dataframe apis df = spark. save () // Authentication // Using IAM Role based authentication instead of keys df.
load () // Write data to Redshift // Create a new Redshift table with the given dataframe // df = df.
option ( "query", "select col1, col2 from tbl group by col3" ). load () // Load Redshift query results in a Spark dataframe val df : DataFrame = spark. Spark Redshift connector Example Notebook - Scala val jdbcURL = "jdbc:redshift://redshifthost:5439/database?user=username&password=pass" val tempS3Dir = "s3://path/for/temp/data" // Read Redshift table using dataframe apis val df : DataFrame = spark.
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