class_docstr: A collection of data which can be pre-processed in parallel on Spark.
class_docstr_tok: ["A","collection","of","data","which","can","be","pre-processed","in","parallel","on","Spark","."]
docstr: Get number of partitions for this SparkXShards.
  
  :return: number of partitions.
docstr_tok: ["Get","number","of","partitions","for","this","SparkXShards",".",":","return",":","number","of","partitions","."]
code: def num_partitions(self) -> int:
      """
  
      Get number of partitions for this SparkXShards.
  
      :return: number of partitions.
      """
      return self.rdd.getNumPartitions()
  
imports: from py4j.protocol import Py4JError
  from bigdl.orca.data.utils import *
  from bigdl.orca import OrcaContext
  from bigdl.dllib.utils.common import get_node_and_core_number, get_spark_sql_context, get_spark_context
  from bigdl.dllib.utils import nest
  from bigdl.dllib.utils.log4Error import invalidInputError
  import numpy
  from typing import TYPE_CHECKING, Any
  from typing import Callable, Dict, List, Optional, Tuple, Union
label_desc: Use image node_id 14 for calling the SparkXShards obj's underlying member method code with example usage: obj.num_partitions() and returns: self