代码语言:txt 复制 spark = SparkSession.builder.appName("Dynamic Where Clause").getOrCreate() 加载数据源并创建DataFrame: 代码语言:txt 复制 df = spark.read.format("csv").option("header", "true").load("data.csv") 其中,"data.csv"是你要加载的数据源文件路径。 定义动态where子句的条件: ...
from pyspark.sql import SparkSession from pyspark.sql.functions import concat # 创建SparkSession spark = SparkSession.builder.getOrCreate() # 创建示例数据 data = [("John", "Doe"), ("Jane", "Smith"), ("Alice", "Brown")] df = spark.createDataFrame(data, ["first_name", "last_name"...
使用sql表达式可以把filter换成wheref = spark.createDataFrame([(2, "Alice"), (5, "Bob")], schema=["age", "name"])df.show()+---+---+|age| name|+---+---+| 2|Alice|| 5| Bob|+---+---+df.filter(df.age>=5).show()+---+--...
In this post, I will use a toy data to show some basic dataframe operations that are helpful in working with dataframes in PySpark or tuning the performance of Spark jobs.
Saving a DataFrame in Parquet format createOrReplaceTempView filter Show the distinct VOTER_NAME entries Filter voter_df where the VOTER_NAME is 1-20 characters in length Filter out voter_df where the VOTER_NAME contains an underscore Show the distinct VOTER_NAME entries again 数据框的列操作 wit...
DataFrame column operations 对数据框列的操作 筛选操作 # Show the distinct VOTER_NAME entries voter_df.select(voter_df['VOTER_NAME']).distinct().show(40, truncate=False) 去除重复值 # Filter voter_df where the VOTER_NAME is 1-20 characters in length voter_df = voter_df.filter('length(VOT...
PySpark File to Dataframe-Part 1 PySpark File to Dataframe-Part 2 PySpark DB to Dataframe PySpark Dataframe to File-Part 1 PySpark Dataframe to File-Part 2 PySpark Dataframe to DB PySpark Dataframe Preview-Part 1 PySpark Dataframe Preview-Part 2 PySpark Dataframe Basic Operations PySp...
Use the spark.table() method with the argument "flights" to create a DataFrame containing the values of the flights table in the .catalog. Save it as flights. Show the head of flights using flights.show(). The column air_time contains the duration of the flight in minutes. ...
Further Resources PySpark filter By Example Setup To run our filter examples, we need some example data. As such, we will load some example data into a DataFrame from a CSV file. SeePySpark reading CSV tutorialfor a more in depth look at loading CSV in PySpark. We are not going to cove...
Pyspark Dataframe APIs to solve the problems using Dataframe style APIs. Relevance of Spark Metastore to convert Dataframs into Temporary Views so that one can process data in Dataframes using Spark SQL. Apache Spark Application Development Life Cycle Apache Spark Application Execution Life Cycle and...