How to write dataframe output to a single file with a specific name using Spark

Spark is designed to write out multiple files in parallel. So there may be cases where we need to merge all the part files, remove the success/commit files and write the content to a single file.

This blog helps you to write spark output to a single file.

Using  df.coalesce(1) we can write data to a single file, 

 result_location = "dbfs:///mnt/datalake/unmesha/output/"   df.coalesce(1).write.format("csv").options(header='true').mode("overwrite").save(result_location)

but still you will see _success files.

 

This solution - adding coalesce isn’t sufficient when you want to write data to a file with a specific name.

We are going to achieve this using dbutils

  result_location = "dbfs:///mnt/datalake/unmesha/output/"
     df.coalesce(1).write.format("csv").options(header='true').mode("overwrite").save(result_location)
  files = dbutils.fs.ls(result_location)
  csv_file = [x.path for x in files if x.path.endswith(".csv")][0] 
  dbutils.fs.mv(csv_file, result_location.rstrip('/') + ".csv") 
  dbutils.fs.rm(result_location, recurse = True)

 Above snippet helps you  to write dataframe output to a single file with a specific name.

  

How to append content to a DBFS file using python spark

You can read and write to DBFS files using 'dbutils'

Lets see one example

dbutils.fs.put("dbfs:///mnt/sample.txt", "sample content")

Above command helps to write "sample content" to 'dbfs:///mnt/sample.txt'

Now you have the file in your DBFS location. Lets see how to append content to this file.

In order to do that, you can open the file in append mode.

with  open("/dbfs/mnt/sample.txt", "a") as f:
  f.write("append values")

Now your appended file is ready!!!

 

How to access data in Delta tables

Delta tables can be accessed either by specifying the path on DBFS or by table name.

You can check my previous blog to see how to write delta files here.  I will be using the same example location here.

Option 1 : Read delta tables by specifying DBFS path

val employeeDF = spark.read.format("delta").load("/mnt/delta/Employee")

Option 2 : Read delta table by  table name

val employeeDF = spark.table("employee")

Create Delta table on csv file in python spark

 

You can read files into Dataframe and write out in delta format

Step 1 : Read the input csv

Step 2 : Write the csv to ADLS location using Delta format

Step 3: Create a table on top of it

myCSV= spark.read.csv("/path/to/input/data",header=True,sep=","); 
myCSV.write.format("delta").mode("overwrite").option('overwriteSchema','true').save("/mnt/delta/Employee") 
spark.sql("CREATE TABLE employee USING DELTA LOCATION '/mnt/delta/Employee/'") 

Create Empty Dataframe In Spark - Without Defining Schema

 

There may be cases where we need to initialize a Dataframe without specifying a schema.
Let's see how to do that

empty_DF = sqlContext.createDataFrame(sc.emptyRDD(),StructType([]))

StructType([]) This creates an empty schema for our dataframe.

Create Widget in Databricks Python Notebook

 In order to get some inputs from user we will require widgets in our Azure Databricks notebook.
This blog helps you to create a text based widget in your python notebook.

Syntax 

dbutils.widgets.text(<WidgetID>,<DefaultValue>,<DisplayName>)

Lets see the result of above widget in Notebook.

Oh yeah....our widget got created.
Now lets enter some inputs in the widget.

Now if you check, the code block has already executed and displayed your entered widget value.

You are done.

Go ahead and create one 😊