df.select(df.age.alias('age_value'),'name') 查询某列为null的行: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 from pyspark.sql.functionsimportisnull df=df.filter(isnull("col_a")) 输出list类型,list中每个元素是Row类: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 list=df.collec...
Checks whether a SparkContext is initialized or not.Throws errorifa SparkContext is already running."""withSparkContext._lock:ifnot SparkContext._gateway:SparkContext._gateway=gateway orlaunch_gateway(conf)SparkContext._jvm=SparkContext._gateway.jvm 在launch_gateway (python/pyspark/java_gateway.py) ...
# Select all the unique council voters voter_df = df.select(df["VOTER NAME"]).distinct() #这个是去重的 # Count the rows in voter_df print("\nThere are %d rows in the voter_df DataFrame.\n" % voter_df.count()) # Add a ROW_ID voter_df = voter_df.withColumn('ROW_ID', F.m...
如果我们看一下list_rdd包含什么,我们可以看到它是PythonRDD.scala:52,因此,这告诉我们 Scala 支持的 PySpark 实例已经识别出这是一个由 Python 创建的 RDD,如下所示: list_rdd 这给我们以下输出: PythonRDD[3] at RDD at PythonRDD.scala:52 现在,让我们看看我们可以用这个列表做什么。我们可以做的第一件事...
df.select(df.customerID.alias(“customer_ID”)).show() #取别名 from pyspark.sql.functions import isnull df = df.filter(isnull(“Churn”)) df.show() #查询某列为null的行 df_list = df.collect() print(df_list) #将数据以python的列表格式输出 df[“Partner”,“gender”].describe().show...
1. Select Columns - Example `df = df.select( "customer_id", "customer_name" )` 2. Creating or Replacing a column - Example df = df.withColumn("always_one", F.lit(1)) df = df.withColumn("customer_id_copy",F.col("customer_id")) 3. Rename a column df.withColumnRenamed(<...
示例二 from pyspark.sql import Row from pyspark.sql.functions import explode eDF = spark.createDataFrame([Row( a=1, intlist=[1, 2, 3], mapfield={"a": "b"})]) eDF.select(explode(eDF.intlist).alias("anInt")).show() +---+ |anInt| +---+ | 1| | 2| | 3| +---+ isin...
select( F.concat(df.str, df.int).alias('concat'), # 直接拼接 F.concat_ws('-', df.str, df.int).alias('concat_ws'), # 指定拼接符 ) df_new.show() >>> output Data: >>> +---+---+ | concat|concat_ws| +---+---+ |abcd123| abcd-123| +---+---+ 3.3 字符串重复...
agg配合groupBy使用,效果等于select。此时concat_df只有两列:sample_id和feature_list。concat_tuple_df = concat_df.groupBy("sample_id","sample_date").agg(collect_list(struct("feature","owner")).alias("tuple"))# 将同sample_id, sample_date的行聚合成组, (feature, owner)两个字段拼成一个单位,组...
.. note:: Experimental."""withSCCallSiteSync(self._sc)ascss:sock_info = self._jdf.collectAsArrowToPythonreturnlist(_load_from_socket(sock_info, ArrowStreamSerializer)) 这里面使用了ArrowStreamSerializer,而ArrowStreamSerializer定义为 classArrowStreamSerializer(Serializer):"""Serializes Arrow record ba...