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pyspark - How to use AND or OR condition in when in Spark - Stack Overflow
107 pyspark.sql.functions.when takes a Boolean Column as its condition. When using PySpark, it's often useful to think "Column Expression" when you read "Column". Logical operations on PySpark columns use the bitwise operators: & for and | for or ~ for not When combining these with comparison operators such as <, parenthesis are often needed.
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Comparison operator in PySpark (not equal/ !=) - Stack Overflow
The selected correct answer does not address the question, and the other answers are all wrong for pyspark. There is no "!=" operator equivalent in pyspark for this solution.
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python - Spark Equivalent of IF Then ELSE - Stack Overflow
python apache-spark pyspark apache-spark-sql edited Dec 10, 2017 at 1:43 Community Bot 1 1
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PySpark: multiple conditions in when clause - Stack Overflow
39 when in pyspark multiple conditions can be built using & (for and) and | (for or). Note:In pyspark t is important to enclose every expressions within parenthesis () that combine to form the condition
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Pyspark: display a spark data frame in a table format
Pyspark: display a spark data frame in a table format Asked 9 years, 3 months ago Modified 2 years, 4 months ago Viewed 413k times
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How to resolve this error: Py4JJavaError: An error occurred while ...
Currently I'm doing PySpark and working on DataFrame. I've created a DataFrame: from pyspark.sql import * import pandas as pd spark = SparkSession.builder.appName(&quot;DataFarme&quot;).getOrCreate...
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spark dataframe drop duplicates and keep first - Stack Overflow
2 I just did something perhaps similar to what you guys need, using drop_duplicates pyspark. Situation is this. I have 2 dataframes (coming from 2 files) which are exactly same except 2 columns file_date (file date extracted from the file name) and data_date (row date stamp).
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Best way to get the max value in a Spark dataframe column
Remark: Spark is intended to work on Big Data - distributed computing. The size of the example DataFrame is very small, so the order of real-life examples can be altered with respect to the small example. Slowest: Method_1, because .describe("A") calculates min, max, mean, stddev, and count (5 calculations over the whole column). Medium: Method_4, because, .rdd (DF to RDD transformation) slows ...
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How to check if spark dataframe is empty? - Stack Overflow
4 On PySpark, you can also use this bool(df.head(1)) to obtain a True of False value It returns False if the dataframe contains no rows
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python - Concatenate two PySpark dataframes - Stack Overflow
Utilize simple unionByName method in pyspark, which concats 2 dataframes along axis 0 as done by pandas concat method. Now suppose you have df1 with columns id, uniform, normal and also you have df2 which has columns id, uniform and normal_2. In order to get a third df3 with columns id, uniform, normal, normal_2.