Spark Dataframe Replace Empty String


I would like to add several columns to a spark (actually pyspark) dataframe , these columns all being functions of several input columns in the df. It uses data on taxi trips, which is provided by New York City. I am trying to get rid of white spaces from column names - because otherwise the DF cannot be saved as parquet file - and did not find any usefull method for renaming. Delta Lake supports most of the options provided by Apache Spark DataFrame read and write APIs for performing batch reads and writes on tables. Check out this post for example of how to process JSON data from Kafka using Spark Streaming. 1 – see the comments below]. From Webinar Jump Start into Apache Spark and Databricks: Is the join happening in Spark or python interpreter on the driver node for the AdTech Sample Notebook? 1 Answer applying a schema to a dataframe 1 Answer. DataFrame class with a few added. apply factory method or Dataset. x: A spark_connection, ml_pipeline, or a tbl_spark. io Since the OneHotEncoder does not accept empty string for name, or you'll get the. Spark Dataframe WHERE Filter Hive Date Functions - all possible Date operations Spark Dataframe - Distinct or Drop Duplicates How to Subtract TIMESTAMP-DATE-TIME in HIVE Spark Dataframe NULL values Spark Dataframe LIKE NOT LIKE RLIKE Hive - BETWEEN Spark Dataframe Replace String SPARK Dataframe Alias AS. It bridges the gap between the simple HBase Key Value store and complex relational SQL queries and enables users to perform complex data analytics on top of HBase using Spark. As an extension to the existing RDD API, DataFrames features seamless integration with all big data tooling and infrastructure via Spark. Here's an easy example of how to rename all columns in an Apache Spark DataFrame. As you can see, there are some blank rows. Need of Dataset in Spark. scala - How to change column types in Spark SQL's DataFrame? 2. If i set missing values to null - then dataframe aggregation works properly, but in. If the name on the tag is the empty. The Spark driver connects to SQL DW using JDBC with a username and password. Spark Dataframe WHERE Filter Hive Date Functions - all possible Date operations How to Subtract TIMESTAMP-DATE-TIME in HIVE Spark Dataframe NULL values SPARK Dataframe Alias AS SPARK-SQL Dataframe How to implement recursive queries in Spark? Spark Dataframe - Distinct or Drop Duplicates. Replace null values in Spark DataFrame. The value must be of the following type: Int, Long, Float, Double, String. Not right or wrong, just easier for me. Only Spark version: 2. I am using PySpark through Spark 1. Underlying processing of dataframes is done by RDD's , Below are the most used ways to create the dataframe. Similar to coalesce defined on an :class:`RDD`, this operation results in a narrow dependency, e. SQLite is a database engine that makes it simple to store and work with relational data. ptype Optionally, supply a data frame prototype for the output cols, overriding the default that will be guessed from the combination of individual values. Create an Empty Spark Dataset / Dataframe using Java Published on December 11, 2016 December 11, 2016 • 11 Likes • 0 Comments. I want to convert all empty strings in all columns to null (None, in Python). Find minimum and maximum value of all columns from Pandas DataFrame; Change data type of a specific column of a pandas DataFrame; How to check whether a pandas DataFrame is empty? If value in row in DataFrame contains string create another column equal to string in Pandas; Filter multiple rows using isin in DataFrame. For grouping by percentiles, I suggest defining a new column via a user-defined function (UDF), and using groupBy on that column. Possible values are latex, html, markdown, pandoc, and rst; this will be automatically determined if the function is called within knitr; it can also be set in the global option knitr. CAST function in SparkR making values NULL when converting String to Timestamp contains Timestamps which are being loaded as String. lets see an example of startswith() Function in pandas python. The second argument 1 represents rows, if it is 2 then the function would apply on columns. 0) Program to load a CSV file into a Dataset using Java 8. A shuffle of two strings is formed by interspersing the characters into a new string, keeping the characters of each string in order. 9 5 0 0 0 6 0 0 0 0. I am facing an issue here that I have a dataframe with 2 columns, "ID" and "Amount". The data set used by this notebook is from 2016 Green Taxi Trip Data. Spark Dataframe WHERE Filter Hive Date Functions - all possible Date operations Spark Dataframe - Distinct or Drop Duplicates How to Subtract TIMESTAMP-DATE-TIME in HIVE Spark Dataframe NULL values Spark Dataframe LIKE NOT LIKE RLIKE Hive - BETWEEN Spark Dataframe Replace String SPARK Dataframe Alias AS. The String class represents character strings. Finally, you can create a bound Column using the Dataset the column is supposed to be part of using Dataset. Sort a Data Frame by Column. Father Jerry ended his homily with the following Easter greeting— "may you leave behind you a string of empty tombs!" Tune in to hear just what he meant by that unconventional Easter greeting. On April 23, 2015, Ocean changed his legal name to Frank Ocean. In this notebook we're going to go through some data transformation examples using Spark SQL. To do this, I have been utilizing pandas. If i set missing values to null - then dataframe aggregation works properly, but in. dropna (axis = 0, how = 'any', thresh = None, subset = None, inplace = False) Technically you could run MyDataFrame. The Scala foldLeft method can be used to iterate over a data structure and perform multiple operations on a Spark DataFrame. scala - Querying Spark SQL DataFrame with complex types; 4. 4) def coalesce (self, numPartitions): """ Returns a new :class:`DataFrame` that has exactly `numPartitions` partitions. # import pandas import pandas as pd. The below creates a data set with the correct structure:-----import org. sparsify: bool, optional, default True. Of course, Spark SQL also supports reading existing Hive tables that are already stored as Parquet but you will need to configure Spark to use Hive’s metastore to load all that information. Delta Lake supports most of the options provided by Apache Spark DataFrame read and write APIs for performing batch reads and writes on tables. Read rendered documentation, see the history of any file, and collaborate with contributors on projects across GitHub. There are indeed multiple ways to apply such a condition in Python. Spark DataFrame columns support arrays and maps, which are great for data sets that have an arbitrary length. md Leave empty to retrieve all the java. com/entries/git-diff-reference-and-examples. Annotations @Stable Since. The value must be of the following type: Int, Long, Float, Double, String. if you go from 1000 partitions to 100 partitions, there will not be a shuffle, instead each of the 100 new partitions will claim 10 of the current partitions. One of the most disruptive areas of change is around the representation of data sets. repartition(x), x: can be no of partitions or even the column name on which you want to partition the data. Pandas is one of those packages and makes importing and analyzing data much easier. Now, the wine_df_2 DataFrame has the columns in the order that I wanted. [sql] Dataframe how to check null values. scala - Is there better way to display entire Spark SQL DataFrame? 3. So Python 3. DynamicFrame Class. In Spark, you have sparkDF. 8, "Replacing Patterns in Scala Strings. The reason is that Hadoop framework is based on a simple programming model (MapReduce) and i. LEFT JOIN will keep records from the left table in case no association matches it. Attachments: Up to 2 attachments (including images) can be used with a maximum of 524. Characteristics. frame() creates data frames, tightly coupled collections of variables which share many of the properties of matrices and of lists, used as the fundamental data structure by most of R 's modeling software. An R interface to Spark. Luckily, Python's string module comes with a replace() method. Scala String FAQ: How do I replace a regular expression (regex) pattern in a String in Scala? Solution. A2A: I would use the replace() method: [code]>>> import pandas as pd >>> import numpy as np >>> df = pd. This is possible in Spark SQL Dataframe easily using regexp_replace or translate function. Replace the logger. Pandas rename() method is used to rename any index, column or row. Python’s pandas library provide a constructor of DataFrame to create a Dataframe by passing objects i. Before converting, I need to check if it has blank values then convert it to NULL. saveAsTable("") Another option is to let Spark SQL manage the metadata, while you control the data location. toPandas calls collect on the dataframe and brings the entire dataset into memory on the driver, so you will be moving data across network and holding locally in memory, so this should only be called if the DF is small enough to store locally. to replace an existing column after the. This is a very rich function as it has many variations. The CSV format is the common file format which gets used as a source file in most of the cases. The Apache Spark Dataset API provides a type-safe, object-oriented programming interface. The new Spark DataFrames API is designed to make big data processing on tabular data easier. As a generic example, say I want to return a new column called "code" that returns a code based on the value of "Amt". I want to convert all empty strings in all columns to null (None, in Python). You can vote up the examples you like and your votes will be used in our system to product more good examples. Feature: Issue 10227 Change-Id. toPandas (df) ¶. nan,0) Let's now review how to apply each of the 4 methods using simple examples. If you want to search single value in whole dataframe [code]yourValue = randomNumber for cols in df. DataFrame([[1, np. For example, regexp_replace("foobar", "oo|ar", "") returns 'fb. Introduction to Datasets. 5 alone; so, we thought it is a good time for revisiting the subject, this time also utilizing the external package spark-csv, provided by Databricks. Join GitHub today. The save is method on DataFrame allows passing in a data source type. [EDIT: Thanks to this post, the issue reported here has been resolved since Spark 1. Ask Question Asked 3 years, 11 months ago. Personally I would go with Python UDF and wouldn't bother with anything else: Vectors are not native SQL types so there will be performance overhead one way or another. length res18: Int = 1 {code} Case 2 {code:java} scala> val anySchema = StructType(StructField("anyName", StringType, nullable = false) :: Nil) anySchema: org. Re: Spark SQL DataFrame: Nullable column and filtering: Date: Thu, 30 Jul 2015 20:58:02 GMT: Perhaps I'm missing what you are trying to accomplish, but if you'd like to avoid the null values do an inner join instead of an outer join. It does not affect the data frame column values. index_names: bool, optional, default True. Like traditional database operations, Spark also supports similar operations on columns. Arguments x. 5, including new built-in functions, time interval literals, and user-defined aggregation function interface. Replace value in csv python I have a csv file with 17 columns and million rows. Yep, it's a little thorny but maybe you can just replace the empty string with something sure to be different than other values. EDIT : in spark. 3+ there is only one API for both Java and Scala, previous versions had dedicated APIs in particular with regards to data types. In Spark SQL dataframes also we can replicate same functionality by using WHEN clause multiple times, once for each conditional check. I am trying to get rid of white spaces from column names - because otherwise the DF cannot be saved as parquet file - and did not find any usefull method for renaming. Spark SQL - DataFrames - A DataFrame is a distributed collection of data, which is organized into named columns. This is possible in Spark SQL Dataframe easily using regexp_replace or translate function. To the best of my knowledge, the difference in the behaviour between these two cases is because of the following : case 1 {code:java} scala> List. The two DataFrames are not required to have the same set of columns. This post describes the bug fix, explains the correct treatment per the CSV…. Derive new column from an existing column. The data is still. The below creates a data set with the correct structure:-----import org. We are creating a spark app that will run locally and will use as many threads as there are cores using local[*]:. Problem: How to create a Spark DataFrame with Array of struct column using Spark and Scala? Using StructType and ArrayType classes we can create a DataFrame with Array of Struct column ( ArrayType(StructType) ). Append column to Data Frame (or RDD). 1> RDD Creation a) From existing collection using parallelize meth. drop ( 'name' , axis = 1 ) # Return the square root of every cell in the dataframe df. Create an Empty Spark Dataset / Dataframe using Java Published on December 11, 2016 December 11, 2016 • 11 Likes • 0 Comments. import org. Reads from a Spark Table into a Spark DataFrame. Cheat sheet for Python dataframe ↔ R dataframe syntax conversions A mini-guide for those who're familiar with data analysis using either Python or R and want to quickly learn the basics for the other language. The rest looks like regular SQL. Spark SQL - Quick Guide - Industries are using Hadoop extensively to analyze their data sets. This means, we do not input a Spark Dataframe, but a string or an Array of strings instead, to be annotated. dropna (axis = 0, how = 'any', thresh = None, subset = None, inplace = False) Technically you could run MyDataFrame. INNER JOIN will filter out records which don't match. Use Spark Structured Streaming. Replace null values in Spark DataFrame. In SQL, if we have to check multiple conditions for any column value then we use case statament. In particular this process requires two steps where data is first converted from external type to row, and then from row to internal representation using generic RowEncoder. in; Home / 0. drop_duplicates Return DataFrame with duplicate rows removed, optionally only considering certain columns. DataFrame has a support for wide range of data format and sources. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. In this chapter, we will walk you through using Spark Streaming to process live data streams. To illustrate this concept better, I remove all the duplicate rows from the "density" column and change the index of wine_df DataFrame to 'density'. def persist (self, storageLevel = StorageLevel. For example, I have a dataset that incorrectly includes empty strings where there should be None values. It can also handle Petabytes of data. Now, the wine_df_2 DataFrame has the columns in the order that I wanted. For a DataFrame a dict of values can be used to specify which value to use for each column (columns not in the dict will not be filled). Need of Dataset in Spark. Is there any function in spark sql to do the same? Announcement! Career Guide 2019 is out now. Default no of partitions in spark is 200, it can be changed based on your requirement. A2A: I would use the replace() method: [code]>>> import pandas as pd >>> import numpy as np >>> df = pd. How to Change Schema of a Spark SQL DataFrame? In order to change the schema, I try to create a new DataFrame based on the content of the original DataFrame using. format A character string. csv') # Drop rows with any empty cells my_dataframe. select( $"col1", $"col2", $"col3" cast IntegerType ). It is conceptually equivalent to a table in a relational database or a data frame. When pat is a string and regex is True (the default), the given pat is compiled as a regex. Split() method. It can be of different data types!. If the regex did not match, or the specified group did not match, an empty string is returned. Like traditional database operations, Spark also supports similar operations on columns. I wanted to add the null/empty string test even though the OP asked about the array because the way the question was formulated made me wonder if he's using string type instead of an array (referral to empty). // IMPORT DEPENDENCIES import org. Often you may want to create a new variable either from column names of a pandas data frame or from one of the columns of the data frame. assign() Python Pandas : Replace or change Column & Row index names in DataFrame; How to convert Dataframe column type from string to date time. scala - How to use constant value in UDF of Spark SQL. As an extension to the existing RDD API, DataFrames features seamless integration with all big data tooling and infrastructure via Spark. # Create a dataframe raw_data =. Published on 6 November 2015 , last updated on 6 June 2018. Saving a pandas dataframe as a CSV. Annotations @Stable Since. The append method does not change either of the original DataFrames. Spark SQL manages the relevant metadata, so when you perform DROP TABLE , Spark removes only the metadata and not the data itself. The String class represents character strings. 4 cases to replace NaN values with zero's in pandas DataFrame Case 1: replace NaN values with zero's for a column using pandas. Lyrics to 'Spark' by Wild Colonials. In the middle of the code, we are following Spark requirements to bind DataFrame to a temporary view. The easiest way to create an empty data frame is probably by just assigning a data. For example, I have a dataset that incorrectly includes empty strings where there should be None values. Spark SQLContext allows us to connect to different Data Sources to write or read data from them, but it has limitations, namely that when the program ends or the Spark shell is closed, all links to the datasoruces we have created are temporary and will not be available in the next session. Hi, I am creating a new Dataframe from an existing dataframe, but need to add new column ("field1" in below code. x An R object, typically a matrix or data frame. iloc and loc Now, let's see how to use. sql(''' SELECT CAST(a['b'] AS STRING) FROM table ''') Its more code in the simple case but I have found in the past that when this is combined into a much more complex query the SQL format can be more friendly from a readability standpoint. This chapter summarises the most important data structures in base R. Maybe the system sees nulls (' ') between the letters of the strings of the non empty cells. Let us first load the pandas library and create a pandas dataframe from multiple lists. It converts MLlib Vectors into rows of scipy. CAST function in SparkR making values NULL when converting String to Timestamp contains Timestamps which are being loaded as String. charAt(0) which will get the first character of the word in upper case (which will be considered as a group). 0 used the RDD API but in the past twelve months, two new alternative and incompatible APIs have been introduced. We will cover the brief introduction of Spark APIs i. I wrote two functions to fill all the empty cells with a 0 and where possible change the value to an integer, but when I run them nothing changes to my dataframe. In Scala, we will use. Extract sub-command from AuditLog events This will allow a better normalization of the data and a better understanding of Gerrit usage. Learn how to append to a DataFrame in Databricks. Nulls and Empty Strings in a Partitioned Column Save as Nulls Apache Spark, Spark, and the Spark logo are. 8 0 0 0 0 8 0. Attachments: Up to 2 attachments (including images) can be used with a maximum of 524. You might already know Apache Spark as a fast and general engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing. I have a data frame with n number of columns and I want to replace empty strings in all these columns with nulls. I wrote two functions to fill all the empty cells with a 0 and where possible change the value to an integer, but when I run them nothing changes to my dataframe. Following is the way, I did:. Spark DataFrame supports reading data from popular professional formats, default types are assumed to be “strings”. So far, we’ve used the DIT to easily discover the missing values in our dataset and to remove/replace the missing values. inplace: bool, default False. And we have provided running example of each functionality for better support. Derive new column from an existing column. scala into a script make the following changes: You won’t need the context, since it is created when the shell is launched, comment that line out. An R tutorial on the concept of data frames in R. Resources; DataFrame from pandas; DataFrame from CSV files; DataFrame from JSON files; DataFrame from SQLite3; DataSets; Spark. 03/15/2017; 31 minutes to read +6; In this article. The Spark driver connects to SQL DW using JDBC with a username and password. bfill is a method that is used with fillna function to back fill the values in a dataframe. Load gapminder data set. Below I implement a custom pandas. This example demonstrates how to use Spark Structured Streaming with Kafka on HDInsight. Pandas is one of those packages and makes importing and analyzing data much easier. hi, I have a vector full of strings like; xy_100_ab xy_101_ab xy_102_ab xy_103_ab I want to seperate each string in three pieces and the separator should be the "_" at the end I want a data. Imputing Null Values. Given a Data Frame, we may not be interested in the entire dataset but only in specific rows. There are indeed multiple ways to apply such a condition in Python. SQLException: No suitable driver found when loading DataFrame into Spark SQL; 5. Characters such as empty strings '' or numpy. Also some of these columns in Hospital_name and State contains 'NAN' values. The new Spark DataFrames API is designed to make big data processing on tabular data easier. the answers suggesting to use cast, FYI, the cast method in spark 1. How to replace null values in Spark DataFrame? 0 votes. DataFrame([1, '', ''], ['a', 'b'. how can i remove commas and dollar sign from a string??? Oct 17, 2012 05:09 PM. duplicated() in Python; Python Pandas : How to add new columns in a dataFrame using [] or dataframe. Change data type of a specific column of a pandas DataFrame Pandas will always store strings as objects. [jira] [Commented] (SPARK-26165) Date and Timestamp column expression is getting converted to string in less than/greater than filter query even though valid date/timestamp string literal is used in the right side filter expression. One of the many new features added in Spark 1. Pyspark replace strings in Spark dataframe column. 0 DataFrames as empty strings and this was fixed in Spark 2. lets see an example of startswith() Function in pandas python. To do this, I have been utilizing pandas. startswith() function in pandas - column starts with specific string in python dataframe In this tutorial we will use startswith() function in pandas, to test whether the column starts with the specific string in python pandas dataframe. String is immutable. Converting a dataframe column from string to datetime. notna¶ DataFrame. 0 Date 2019-05-25 Title Convert Strings into any Case Description A consistent, flexible and easy to use tool to parse and con-vert strings into cases like snake or camel among others. In SQL, if we have to check multiple conditions for any column value then we use case statament. In the implementation of EmptyRDD it returns Array. First create a dataframe with those 3 columns Hourly Rate, Daily Rate and Weekly Rate. GitHub Gist: instantly share code, notes, and snippets. Gather host information. SQLException: No suitable driver found when loading DataFrame into Spark SQL; 5. To overcome the limitations of RDD and Dataframe, Dataset emerged. Arguments x. This is similar to the Spark DataFrame built-in toPandas() method, but it handles MLlib Vector columns differently. 6 behavior regarding string literal parsing. On this post, I will walk you through commonly used Spark DataFrame column operations. Lyrics to 'Spark' by Wild Colonials. ErrorIfExists as the save mode. The spark session read table will create a data frame from the whole table that was stored in a disk. Let us get started with some examples from a real world data set. 8 0 0 0 0 8 0. Use Spark Structured Streaming. In this section, we look at various features of the F# data frame library (using both Series and Frame types and modules). Find more information, and his slides, here. A Spark DataFrame is a distributed collection of data organized into named columns that provides operations. I need to concatenate two columns in a dataframe. UDFs are great when built-in SQL functions aren’t sufficient, but should be used sparingly because they’re. Apache Spark is evolving at a rapid pace, including changes and additions to core APIs. In November 2014, it was revealed that the name change had not been legalized due to multiple speeding offenses. Non-missing values get mapped to True. Let’s first create our own CSV file using the data that is currently present in the DataFrame, we can store the data of this DataFrame in CSV format using the API called to_csv() of Pandas DataFrame as. The first layer added to an empty data frame sets the coordinate system for the data frame, but you can change it if necessary. Resources; DataFrame from pandas; DataFrame from CSV files; DataFrame from JSON files; DataFrame from SQLite3; DataSets; Spark. Program to load a text file into a Dataset in Spark using Java 8. notna¶ DataFrame. For that I must convert the strings to float values. Replacing Python Strings Often you'll have a string (str object), where you will want to modify the contents by replacing one piece of text with another. the answers suggesting to use cast, FYI, the cast method in spark 1. If search is not found in str, str is returned unchanged. IllegalArgumentException: Unsupported value type java. Just like pandas dropna() method manage and remove Null values from a data frame, fillna() manages and let the user replace NaN values with some value of their own. use_inf_as_na = True). 6 behavior regarding string literal parsing. Data Frames Description. With the introduction of window operations in Apache Spark 1. In this third tutorial (see the previous one) we will introduce more advanced concepts about SparkSQL with R that you can find in the SparkR documentation, applied to the 2013 American Community Survey housing data. if it's: NULL, zero-length, NA, NaN, FALSE, an empty string or 0. duplicated() in Python; Python Pandas : How to add new columns in a dataFrame using [] or dataframe. I have a dataframe with column as String. Also, used case class to transform the RDD to the data frame. # import pandas import pandas as pd. I am working on the Movie Review Analysis project with spark dataframe using scala. The following are code examples for showing how to use pyspark. 9 0 0 10 0 0 0 0 0 0 0. If you want to search single value in whole dataframe [code]yourValue = randomNumber for cols in df. columnNames is an Array[String] representing the dataframe column names; columnDataTypes is an Array[String] representing Spark column DataTypes; To learn more about Spark DataFrame data types, you can refer to the official documentation. Non-missing values get mapped to True. (Int => String) = v READ MORE. ewm (self[, com, span, halflife, alpha, …]) Provide exponential weighted functions. Even though both of them are synonyms , it is important for us to understand the difference between when to…. This PR enables passing null/None as value in the replacement map in DataFrame. Note that this currently only works with DataFrames that are created from a HiveContext as there is no notion of a persisted catalog in a standard SQL context. A pivot is an aggregation where one (or more in the general case) of the grouping columns has its distinct values transposed into individual columns. While R can read excel. GitHub Gist: instantly share code, notes, and snippets. Spark SQL Tutorial – Understanding Spark SQL With Examples Last updated on May 22,2019 129. In Scala, we will use. The following code examples show how to use org. Here’s how the different functions should be used in general: Use custom. A DataFrame is a Spark Dataset (a distributed, strongly-typed collection of data, the interface was introduced in Spark 1. Possible values are latex, html, markdown, pandoc, and rst; this will be automatically determined if the function is called within knitr; it can also be set in the global option knitr. Spark code can be organized in custom transformations, column functions, or user defined functions (UDFs). I have a dataframe with column as String. This article represents code in R programming language which could be used to create a data frame with column names. hi, I have a vector full of strings like; xy_100_ab xy_101_ab xy_102_ab xy_103_ab I want to seperate each string in three pieces and the separator should be the "_" at the end I want a data. It is very common sql operation to replace a character in a string with other character or you may want to replace string with other string. Here we have taken the FIFA World Cup Players Dataset. nan, 4, 6]]) df We cannot drop single values from a DataFrame; we can only drop full rows or full columns. 2015): added spray-json-shapeless library Update (06. There seems to be no 'add_columns' in spark, and. Also, used case class to transform the RDD to the data frame. For the standard deviation, see scala - Calculate the standard deviation of grouped data in a Spark DataFrame - Stack Overflow. Once we have the DataFrame, we can persist it in a CSV file on the local disk. Minor changes to the UDF API to pass in and return corefxlab DataFrames Accompanying unit test changes Putting it up here to get initial thoughts. 8 3 0 0 0 0 0. Non-missing values get mapped to True. In Spark SQL dataframes also we can replicate same functionality by using WHEN clause multiple times, once for each conditional check. Get Equal to of dataframe and other, element-wise (binary operator eq). frame to write to the workbook. Step 4: Run the Spark Streaming app to process clickstream events. Finally found a solution (or a workaround, don't know exactly how to call it As apparently what I described above was not my fault, in the end, but was due to something that probably broke up since Spark 1. We will use an empty title string as the default vertex attribute to represent the target of a broken link. There is a lot of nice functionality built into the method, but when the number of dataframe rows/columns gets relatively large, to_string starts to tank. Note that strings are loaded as ‘object’ datatypes, because technically, the DataFrame holds a pointer to the string data elsewhere in memory. The most powerful thing about this function is that it can work with Python regex (regular expressions).