pyspark split

可以使用 pyspark 中的 split 函数将字符串按照指定的分隔符进行分割，例如：

from pyspark.sql.functions import split

# 创建一个 DataFrame
df = spark.createDataFrame([(1, "John,Doe"), (2, "Jane,Smith")], ["id", "name"])

# 使用 split 函数将 name 列按照逗号进行分割
df = df.withColumn("first_name", split(df["name"], ",")[0])
df = df.withColumn("last_name", split(df["name"], ",")[1])

# 显示结果
df.show()

输出结果：

+---+---------+----------+
| id|     name|first_name|last_name|
+---+---------+----------+
|  1|  John,Doe|      John|      Doe|
|  2|Jane,Smith|      Jane|    Smith|
+---+---------+----------+---------+

相关问题

org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 830, in main process() File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/python/lib/pyspark.zip/pyspark/worker.py", line 820, in process out_iter = func(split_index, iterator) File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/rdd.py", line 5405, in pipeline_func return func(split, prev_func(split, iterator)) File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/rdd.py", line 5405, in pipeline_func return func(split, prev_func(split, iterator)) File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/rdd.py", line 828, in func return f(iterator) File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/rdd.py", line 3964, in combineLocally merger.mergeValues(iterator) File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/python/lib/pyspark.zip/pyspark/shuffle.py", line 256, in mergeValues for k, v in iterator: File "/Users/zzs/PycharmProjects/pythonProject/venv/lib/python3.10/site-packages/pyspark/python/lib/pyspark.zip/pyspark/util.py", line 81, in wrapper return f(*args, **kwargs) File "/Users/zzs/PycharmProjects/pythonProject/pyspark项目练习/项目练习2.py", line 7, in <lambda> json_str_file = file_rdd.flatMap(lambda x: x.spilt("|")) AttributeError: 'str' object has no attribute 'spilt' at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:561) at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:767) at org.apache.spark.api.python.PythonRunner$$anon$3.read(PythonRunner.scala:749) at org.apache.spark.api.python.BasePythonRun

这个错误是由于在代码的第7行中使用了错误的方法名。正确的方法名应该是`split`而不是`spilt`。`split`方法用于将字符串分割为一个列表。将第7行代码修改为以下内容应该可以解决问题：

json_str_file = file_rdd.flatMap(lambda x: x.split("|"))

请注意，`split`方法的参数是分割符，根据你的需求可能需要使用不同的分割符。

pyspark concat

在PySpark中，使用concat函数可以将多个列的值合为一个列。引用中的示例代码展示了如何使用concat函数。首先，我们需要创建一个SparkSession并读取CSV文件。然后，使用withColumn方法将要拼接的列传递给concat函数，并指定拼接后的新列的名称。最后，使用show方法来展示结果。

以下是一个示例代码：

from pyspark.sql import SparkSession
from pyspark.sql.functions import concat

spark = SparkSession.builder.master("local").appName("concat_example").getOrCreate()

# 读取CSV文件
df = spark.read.csv("./demo.csv", inferSchema=True, header=True)

# 使用concat函数将gid和score列合并为一个新列
df_concat = df.withColumn("concat_column", concat(df["gid"], df["score"]))

# 展示结果
df_concat.show()

执行以上代码后，将会展示包含合并列的数据框。

请注意，示例中的concat函数仅演示了将两列合并为一个新列的情况。如果要合并多个列，只需在concat函数中添加更多的列参数即可。

引用中的代码展示了如何使用split函数将一个包含分隔符的字符串列拆分为多个列。可以将split函数与concat函数一起使用，将多列拆分后再进行合并。

希望这个解答对你有所帮助！<em>1</em><em>2</em>
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