class_docstr: Partially defined over window with partitioning.
class_docstr_tok: ["Partially","defined","over","window","with","partitioning","."]
docstr: Specifies the time attribute on which rows are ordered.
  
  For streaming tables, reference a rowtime or proctime time attribute here
  to specify the time mode.
  
  For batch tables, refer to a timestamp or long attribute.
  
  :param order_by: Field reference.
  :return: An over window with defined order.
docstr_tok: ["Specifies","the","time","attribute","on","which","rows","are","ordered",".","For","streaming","tables",",","reference","a","rowtime","or","proctime","time","attribute","here","to","specify","the","time","mode",".","For","batch","tables",",","refer","to","a","timestamp","or","long","attribute",".",":","param","order_by",":","Field","reference",".",":","return",":","An","over","window","with","defined","order","."]
code: def order_by(
      self, order_by: Expression
  ) -> "OverWindowPartitionedOrdered":
      """
      Specifies the time attribute on which rows are ordered.
  
      For streaming tables, reference a rowtime or proctime time attribute here
      to specify the time mode.
  
      For batch tables, refer to a timestamp or long attribute.
  
      :param order_by: Field reference.
      :return: An over window with defined order.
      """
      return OverWindowPartitionedOrdered(
          self._java_over_window.orderBy(_get_java_expression(order_by))
      )
  
imports: from py4j.java_gateway import get_method
  from pyflink.java_gateway import get_gateway
  from pyflink.table import Expression
  from pyflink.table.expression import _get_java_expression
  from pyflink.table.utils import to_expression_jarray
label_desc: Use image node_id 2 for calling the OverWindowPartitioned obj's underlying member method code with example usage: obj.order_by(order_by) and returns: OverWindowPartitionedOrdered