Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. #88Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about TeamsJun 23, 2017 · For more information, see SPARK-5063. (2) When a Spark Streaming job recovers from checkpoint, this exception will be hit if a reference to an RDD not defined by the streaming job is used in DStream operations. For more information, See SPARK-13758. The creation and usage of the broadcast variables for the data that is shared across the multiple stages and tasks. The broadcast variables are not sent to the executors with "sc. broadcast (variable)" call instead they will be sent to the executors when they are first used. The PySpark Broadcast variable is created using the "broadcast (v ...Error: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transforamtion. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. Instead of that official documentation recommends something like this:SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. For understanding a bit better what I am trying to do, let me give an example illustrating a possible use case : Lets say given_df is a dataframe of sentences, where each sentence consist of some words separated by space.Details. _pickle.PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.SPARK-5063 relates to better error messages when trying to nest RDD operations, which is not supported. It's a usability issue, not a functional one. The root cause is the nesting of RDD operations and the solution is to break that up. Here we are trying a join of dRDD and mRDD.Nov 11, 2017 · For more information, see SPARK-5063. edit: It seems the issue is that sklearn cross_validate() clones the estimator for each fit in a fashion similar to pickling the estimator object which is not allowed for PySpark GridsearchCV estimator because a SparkContext() object cannot/should not be pickled. Aug 21, 2017 · I downloaded a file and now I'm trying to write it as a dataframe to hdfs. import requests from pyspark import SparkContext, SparkConf conf = SparkConf().setAppName('Write Data').setMaster('loca... def localCheckpoint (self): """ Mark this RDD for local checkpointing using Spark's existing caching layer. This method is for users who wish to truncate RDD lineages while skipping the expensive step of replicating the materialized data in a reliable distributed file system.Mar 6, 2023 · Cannot create pyspark dataframe on pandas pipelinedRDD. list_of_df = process_pitd_objects (objects) # returns a list of dataframes list_rdd = sc.parallelize (list_of_df) spark_df_list = list_rdd.map (lambda x: spark.createDataFrame (x)).collect () So I have a list of dataframes in python and I want to convert each dataframe to pyspark. Mar 6, 2023 · Cannot create pyspark dataframe on pandas pipelinedRDD. list_of_df = process_pitd_objects (objects) # returns a list of dataframes list_rdd = sc.parallelize (list_of_df) spark_df_list = list_rdd.map (lambda x: spark.createDataFrame (x)).collect () So I have a list of dataframes in python and I want to convert each dataframe to pyspark. Jul 7, 2022 · SPARK-5063 relates to better error messages when trying to nest RDD operations, which is not supported. ⭐ It's a usability issue, not a functional one. ⭐The root cause is the nesting of RDD operat... Programming Language Abap ActionScript Assembly BASIC C C# C++ Clojure Cobol CSS Dart Delphi Elixir Erlang F# Fortran Go Groovy Haskell pyspark.SparkContext.broadcast. ¶. SparkContext.broadcast(value: T) → pyspark.broadcast.Broadcast [ T] [source] ¶. Broadcast a read-only variable to the cluster, returning a Broadcast object for reading it in distributed functions. The variable will be sent to each cluster only once. New in version 0.7.0. Parameters. valueT.pyspark.SparkContext.broadcast. ¶. SparkContext.broadcast(value: T) → pyspark.broadcast.Broadcast [ T] [source] ¶. Broadcast a read-only variable to the cluster, returning a Broadcast object for reading it in distributed functions. The variable will be sent to each cluster only once. New in version 0.7.0. Parameters. valueT.For more information, see SPARK-5063. I've played with this a bit, and it seems to reliably occur anytime I try to map a class method to an RDD within the class. I have confirmed that the mapped function works fine if I implement outside of a class structure, so the problem definitely has to do with the class.Jul 25, 2020 · Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about Teams pyspark.SparkContext.broadcast. ¶. SparkContext.broadcast(value: T) → pyspark.broadcast.Broadcast [ T] [source] ¶. Broadcast a read-only variable to the cluster, returning a Broadcast object for reading it in distributed functions. The variable will be sent to each cluster only once. New in version 0.7.0. Parameters. valueT.Above example first creates a DataFrame, transform the data using broadcast variable and yields below output. You can also use the broadcast variable on the filter and joins. Below is a filter example. # Broadcast variable on filter filteDf= df.where((df['state'].isin(broadcastStates.value)))Jan 21, 2019 · Thread Pools. One of the ways that you can achieve parallelism in Spark without using Spark data frames is by using the multiprocessing library. The library provides a thread abstraction that you can use to create concurrent threads of execution. However, by default all of your code will run on the driver node. Jan 2, 2020 · PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. Feb 1, 2021 · I am getting the following error: PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. Is there any way to run a SQL query for each row of a dataframe in PySpark?Description Spark does not support nested RDDs or performing Spark actions inside of transformations; this usually leads to NullPointerExceptions (see SPARK-718 as one example). The confusing NPE is one of the most common sources of Spark questions on StackOverflow: For more information, see SPARK-5063. During handling of the above exception, another exception occurred: raise pickle.PicklingError(msg) _pickle.PicklingError: Could not serialize broadcast: RuntimeError: It appears that you are attempting to reference SparkContext from a broadcast variable, .. etcI want to broadcast a hashmap in Python that I would like to use for lookups on worker nodes. class datatransform: # Constructor def __init__(self, lookupFileName, dataFileName): ...Jul 27, 2021 · For more information, see SPARK-5063. The objective of this piece of code is to create a flag for every row based on the date differences. Multiple rows per user are supplied to the function to create the values of the flag. org.apache.spark.SparkException: RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map (x => rdd2.values.count () * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063.For more information, see SPARK-5063. _pickle.PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. 代码RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(lambda x: rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063. Feb 1, 2021 · I am getting the following error: PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. The issue is that, as self._mapping appears in the function addition, when applying addition_udf to the pyspark dataframe, the object self (i.e. the AnimalsToNumbers class) has to be serialized but it can’t be. A (surprisingly simple) way is to create a reference to the dictionary ( self._mapping) but not the object: AnimalsToNumbers (spark ...The preservesPartitioning = true tells Spark that this map function doesn't modify the keys of rdd2; this will allow Spark to avoid re-partitioning rdd2 for any subsequent operations that join based on the (t, w) key. This broadcast could be inefficient since it involves a communications bottleneck at the driver. For more information, see SPARK-5063. As the error says, i'm trying to map (transformation) a JavaRDD object within the main map function, how is it possible with Apache Spark? The main JavaPairRDD object (TextFile and Word are defined classes): JavaPairRDD<TextFile, JavaRDD<Word>> filesWithWords = new... and map function:RuntimeError: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. Labels: Broadcast variable. Sparkcontext. 2_image.png.png. 37 KB.RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(lambda x: rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063.I want to broadcast a hashmap in Python that I would like to use for lookups on worker nodes. class datatransform: # Constructor def __init__(self, lookupFileName, dataFileName): ...spark.sql("select * from test") --need to pass select values as intput values to same function --used pandas df for calling function – pythonUser Feb 24, 2021 at 16:08Spark: Broadcast variables: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transforamtion. 0.Nov 15, 2015 · I want to broadcast a hashmap in Python that I would like to use for lookups on worker nodes. class datatransform: # Constructor def __init__(self, lookupFileName, dataFileName): ... Jul 14, 2015 · Spark: Broadcast variables: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transforamtion. 0. Feb 1, 2021 · I am getting the following error: PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. Aug 21, 2017 · I downloaded a file and now I'm trying to write it as a dataframe to hdfs. import requests from pyspark import SparkContext, SparkConf conf = SparkConf().setAppName('Write Data').setMaster('loca... SPARK-5063 relates to better error messages when trying to nest RDD operations, which is not supported. It's a usability issue, not a functional one. The root cause is the nesting of RDD operations and the solution is to break that up. Here we are trying a join of dRDD and mRDD.RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(lambda x: rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063.For more information, see SPARK-5063. · Issue #88 · maxpumperla/elephas · GitHub maxpumperla / elephas Public Closed on Jun 26, 2018 · 18 comments mohaimenz on Jun 26, 2018Jul 21, 2020 · For more information, see SPARK-5063. Super simple EXAMPLE app to try and run some calculations in parallel. Works (sometimes) but most times crashes with the above exception. RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(lambda x: rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063. Jul 21, 2020 · For more information, see SPARK-5063. Super simple EXAMPLE app to try and run some calculations in parallel. Works (sometimes) but most times crashes with the above exception. Aug 28, 2018 · SparkContext can only be used on the driver. When you invoke map you are on an Executor. The link I sent you runs parallel collection and is invoked from the Driver, also doing some zipping stuff. I discussed this with that person on that question as that is what became of it. That is the correct approach imho. Apr 23, 2015 · SPARK-5063 relates to better error messages when trying to nest RDD operations, which is not supported. It's a usability issue, not a functional one. The root cause is the nesting of RDD operations and the solution is to break that up. Here we are trying a join of dRDD and mRDD. df = spark.createDataFrame(data,schema=schema) Now we do two things. First, we create a function colsInt and register it. That registered function calls another function toInt (), which we don’t need to register. The first argument in udf.register (“colsInt”, colsInt) is the name we’ll use to refer to the function.SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. For understanding a bit better what I am trying to do, let me give an example illustrating a possible use case : Lets say given_df is a dataframe of sentences, where each sentence consist of some words separated by space.SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. from pyspark import SparkContext from awsglue.context import GlueContext from awsglue.transforms import SelectFields import ray import settings sc = SparkContext.getOrCreate () glue_context = GlueContext (sc) @ray.remote def ...I am trying to write a function in Azure databricks. I would like to spark.sql inside the function. But it looks like I cannot use it with worker nodes. def SEL_ID(value, index): # some processing on value here ans = spark.sql("SELECT id FROM table WHERE bin = index") return ans spark.udf.register("SEL_ID", SEL_ID)It's a Spark problem :) When you apply function to Dataframe (or RDD) Spark needs to serialize it and send to all executors. It's not really possible to serialize FastText's code, because part of it is native (in C++). Possible solution would be to save model to disk, then for each spark partition load model from disk and apply it to the data.spark的调试问题. spark运行过程中的数据总是以RDD的方式存储，使用Logger等日志模块时，对RDD内数据无法识别，应先使用行为操作转化为scala数据结构然后输出。. scala Map 排序. 对于scala Map数据的排序，使用 scala.collection.immutable.ListMap 和 sortWiht (sortBy),具体用法如下 ... RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(lambda x: rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063.this rdd lacks a sparkcontext. it could happen in the following cases: . rdd transformations and actions are not invoked by the driver, . but inside of other transformations; for example, rdd1.map(x => rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation I have a function that accepts a spark DataFrame and I would like to obtain the Spark context in which the DataFrames exists. The reason is that I want to get the SQLContext so I can run some SQL queries. sql_Context = SQLContext (output_df.sparkContext ()) sql_Context.registerDataFrameAsTable (output_df, "table1") sql_Context.sql ("select ...broadcast [T] (value: T) (implicit arg0: ClassTag [T]): Broadcast [T] Broadcast a read-only variable to the cluster, returning a org.apache.spark.broadcast.Broadcast object for reading it in distributed functions. The variable will be sent to each cluster only once. You can only broadcast a real value, but an RDD is just a container of values ...Mar 18, 2021 · SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. For understanding a bit better what I am trying to do, let me give an example illustrating a possible use case : Lets say given_df is a dataframe of sentences, where each sentence consist of some words separated by space. May 5, 2022 · Error: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. Without the call of collect the Dataframe url_select_df is distributed across the executors. When you then call map, the lambda expression gets executed on the executors.. Because the lambda expression is calling createDF which is using the SparkContext you get the exception as it is not possible to use the SparkContext on an execPart of AWS Collective. 1. I have created a script locally that uses the spark extension 'uk.co.gresearch.spark:spark-extension_2.12:2.2.0-3.3' for comparing different DataFrames in a simple manner. However, when I try this out on AWS Glue I ran into some issues and received this error: ModuleNotFoundError: No module named 'gresearch'.Sep 30, 2015 · org.apache.spark.SparkException: RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map (x => rdd2.values.count () * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063. For more information, see SPARK-5063. As the error says, i'm trying to map (transformation) a JavaRDD object within the main map function, how is it possible with Apache Spark? The main JavaPairRDD object (TextFile and Word are defined classes): JavaPairRDD<TextFile, JavaRDD<Word>> filesWithWords = new... and map function:def pickleFile (self, name: str, minPartitions: Optional [int] = None)-> RDD [Any]: """ Load an RDD previously saved using :meth:`RDD.saveAsPickleFile` method... versionadded:: 1.1.0 Parameters-----name : str directory to the input data files, the path can be comma separated paths as a list of inputs minPartitions : int, optional suggested minimum number of partitions for the resulting RDD ...Error: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.Jan 3, 2018 · For more information, see SPARK-5063. (2) When a Spark Streaming job recovers from checkpoint, this exception will be hit if a reference to an RDD not defined by the streaming job is used in DStream operations. For more information, See SPARK-13758. Not working even after I revoked it and I'm not using any objects. Code Updated: PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063.SPARK-5063 relates to better error messages when trying to nest RDD operations, which is not supported. It's a usability issue, not a functional one. The root cause is the nesting of RDD operations and the solution is to break that up. Here we are trying a join of dRDD and mRDD.Jul 10, 2020 · Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transforamtion. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. 17. You are passing a pyspark dataframe, df_whitelist to a UDF, pyspark dataframes cannot be pickled. You are also doing computations on a dataframe inside a UDF which is not acceptable (not possible). Keep in mind that your function is going to be called as many times as the number of rows in your dataframe, so you should keep computations ...For more information, see SPARK-5063. _pickle.PicklingError: Could not serialize object: Exception: It appears that you are attempting to reference SparkContext from a broadcast variable, action, or transformation. SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. 代码Throughout this book, we will focus on real-world applications of machine learning technology. While we may briefly delve into some theoretical aspects of machine learning algorithms and required maths for machine learning, the book will generally take a practical, applied approach with a focus on using examples and code to illustrate how to effectively use the features of Spark and MLlib, as ...Create a Function. The first step in creating a UDF is creating a Scala function. Below snippet creates a function convertCase () which takes a string parameter and converts the first letter of every word to capital letter. UDF’s take parameters of your choice and returns a value. val convertCase = (strQuote:String) => { val arr = strQuote ...
def localCheckpoint (self): """ Mark this RDD for local checkpointing using Spark's existing caching layer. This method is for users who wish to truncate RDD lineages while skipping the expensive step of replicating the materialized data in a reliable distributed file system.. 150 90
In this blog, I will teach you the following with practical examples: Syntax of map () Using the map () function on RDD. Using the map () function on DataFrame. map () is a transformation used to apply the transformation function (lambda) on every element of RDD/DataFrame and returns a new RDD. Syntax: dataframe_name.map ()Aug 21, 2017 · I downloaded a file and now I'm trying to write it as a dataframe to hdfs. import requests from pyspark import SparkContext, SparkConf conf = SparkConf().setAppName('Write Data').setMaster('loca... So when you say it should execute self.decode_module() inside the nodes, PySpark tries to pickle the whole (self) object (that contains a reference to the spark context). To fix that, you just need to remove the SparkContext reference from the telco_cn class and use a different approach like using the SparkContext before calling the class ...3. Spark RDD Broadcast variable example. Below is a very simple example of how to use broadcast variables on RDD. This example defines commonly used data (country and states) in a Map variable and distributes the variable using SparkContext.broadcast () and then use these variables on RDD map () transformation. 4.I downloaded a file and now I'm trying to write it as a dataframe to hdfs. import requests from pyspark import SparkContext, SparkConf conf = SparkConf().setAppName('Write Data').setMaster('loca...Oct 10, 2019 · the following code: import dill fnc = lambda x:x dill.dumps(fnc, recurse=False) fails on Databricks notebook with the following error: Exception: It appears that you are attempting to reference Spa... this rdd lacks a sparkcontext. it could happen in the following cases: . rdd transformations and actions are not invoked by the driver, . but inside of other transformations; for example, rdd1.map(x => rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformationMar 18, 2021 · SparkContext can only be used on the driver, not in code that it run on workers. For more information, see SPARK-5063. For understanding a bit better what I am trying to do, let me give an example illustrating a possible use case : Lets say given_df is a dataframe of sentences, where each sentence consist of some words separated by space. Create a Function. The first step in creating a UDF is creating a Scala function. Below snippet creates a function convertCase () which takes a string parameter and converts the first letter of every word to capital letter. UDF’s take parameters of your choice and returns a value. val convertCase = (strQuote:String) => { val arr = strQuote ...Mar 6, 2023 · Cannot create pyspark dataframe on pandas pipelinedRDD. list_of_df = process_pitd_objects (objects) # returns a list of dataframes list_rdd = sc.parallelize (list_of_df) spark_df_list = list_rdd.map (lambda x: spark.createDataFrame (x)).collect () So I have a list of dataframes in python and I want to convert each dataframe to pyspark. Jul 7, 2022 · SPARK-5063 relates to better error messages when trying to nest RDD operations, which is not supported. ⭐ It's a usability issue, not a functional one. ⭐The root cause is the nesting of RDD operat... Programming Language Abap ActionScript Assembly BASIC C C# C++ Clojure Cobol CSS Dart Delphi Elixir Erlang F# Fortran Go Groovy Haskell For more information, see SPARK-5063. apache-spark; apache-spark-sql; pyspark; Share. Improve this question. Follow edited Sep 30, 2019 at 2:52. Pyspark Developer. spark的调试问题. spark运行过程中的数据总是以RDD的方式存储，使用Logger等日志模块时，对RDD内数据无法识别，应先使用行为操作转化为scala数据结构然后输出。. scala Map 排序. 对于scala Map数据的排序，使用 scala.collection.immutable.ListMap 和 sortWiht (sortBy),具体用法如下 ...For more information, see SPARK-5063. The objective of this piece of code is to create a flag for every row based on the date differences. Multiple rows per user are supplied to the function to create the values of the flag.3. Spark RDD Broadcast variable example. Below is a very simple example of how to use broadcast variables on RDD. This example defines commonly used data (country and states) in a Map variable and distributes the variable using SparkContext.broadcast () and then use these variables on RDD map () transformation. 4.The mlflow.spark module provides an API for logging and loading Spark MLlib models. This module exports Spark MLlib models with the following flavors: Spark MLlib (native) format. Allows models to be loaded as Spark Transformers for scoring in a Spark session. Models with this flavor can be loaded as PySpark PipelineModel objects in Python.Above example first creates a DataFrame, transform the data using broadcast variable and yields below output. You can also use the broadcast variable on the filter and joins. Below is a filter example. # Broadcast variable on filter filteDf= df.where((df['state'].isin(broadcastStates.value)))RDD transformations and actions can only be invoked by the driver, not inside of other transformations; for example, rdd1.map(lambda x: rdd2.values.count() * x) is invalid because the values transformation and count action cannot be performed inside of the rdd1.map transformation. For more information, see SPARK-5063.For more information, see SPARK-5063. · Issue #88 · maxpumperla/elephas · GitHub maxpumperla / elephas Public Closed on Jun 26, 2018 · 18 comments mohaimenz on Jun 26, 2018Mar 26, 2020 · For more information, see SPARK-5063. 原因： spark不允许在action或transformation中访问SparkContext，如果你的action或transformation中引用了self，那么spark会将整个对象进行序列化，并将其发到工作节点上，这其中就保留了SparkContext，即使没有显式的访问它，它也会在闭包内被引用 ... def pickleFile (self, name: str, minPartitions: Optional [int] = None)-> RDD [Any]: """ Load an RDD previously saved using :meth:`RDD.saveAsPickleFile` method... versionadded:: 1.1.0 Parameters-----name : str directory to the input data files, the path can be comma separated paths as a list of inputs minPartitions : int, optional suggested minimum number of partitions for the resulting RDD ... .