CODEWITHSUNDEEP
apache-sparkpysparkspark-excel
OMG
OMG

Reputation: 263

Reading Excel (.xlsx) file in pyspark

I am trying to read a .xlsx file from local path in PySpark.

I've written the below code:

from pyspark.shell import sqlContext
from pyspark.sql import SparkSession

spark = SparkSession.builder \
      .master('local') \
      .appName('Planning') \
      .enableHiveSupport() \
      .config('spark.executor.memory', '2g') \
      .getOrCreate()

df = sqlContext.read("C:\P_DATA\tyco_93_A.xlsx").show()

Error:

TypeError: 'DataFrameReader' object is not callable

Upvotes: 12

Views: 57757

Answers (2)

Deva
Deva

Reputation: 66

You could use crealytics package.

Need to add it to spark, either by maven co-ordinates or while starting the spark shell as below.

$SPARK_HOME/bin/spark-shell --packages com.crealytics:spark-excel_2.12:0.13.1

For databricks users- need to add it as a library by navigating Cluster - 'clusterName' - Libraries - Install New - Provide 'com.crealytics:spark-excel_2.12:0.13.1' under maven coordinates.

df = spark.read
     .format("com.crealytics.spark.excel")
     .option("dataAddress", "'Sheet1'!")
     .option("header", "true")
     .option("inferSchema", "true")
     .load("C:\P_DATA\tyco_93_A.xlsx")

More options are available in below github page.

https://github.com/crealytics/spark-excel

Upvotes: 1

Ghost
Ghost

Reputation: 520

You can use pandas to read .xlsx file and then convert that to spark dataframe.

from pyspark.sql import SparkSession
import pandas

spark = SparkSession.builder.appName("Test").getOrCreate()

pdf = pandas.read_excel('excelfile.xlsx', sheet_name='sheetname', inferSchema='true')
df = spark.createDataFrame(pdf)

df.show()

Upvotes: 19

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