pyspark isjson
时间: 2023-07-25 19:07:22 浏览: 38
`pyspark`是一个用于大规模数据处理的Python框架。`isjson`是一个用于判断字符串是否为JSON格式的函数。
在`pyspark`中,可以使用`from_json`函数将JSON字符串转换为`structType`的数据类型。如果要判断一个字符串是否为JSON格式,可以使用`json.loads`函数进行尝试解析,如果解析成功则说明是JSON格式,否则会抛出异常。示例代码如下:
```python
import json
def isjson(str):
try:
json.loads(str)
except ValueError:
return False
return True
```
使用示例:
```python
>>> isjson('{"name": "John", "age": 30}')
True
>>> isjson('{"name": "John", "age": 30')
False
```
相关问题
pyspark解析json数组
Sure, I can help you with that! In PySpark, you can use the `from_json` function from the `pyspark.sql.functions` module to parse JSON arrays. Here's an example code snippet:
```
from pyspark.sql.functions import from_json
from pyspark.sql.types import ArrayType, StringType, StructType, StructField
# Define the schema of your JSON array
schema = StructType([
StructField("name", StringType()),
StructField("age", StringType())
])
# Create a DataFrame with an example JSON array
json_array = [
'{"name": "Alice", "age": "25"}',
'{"name": "Bob", "age": "30"}',
'{"name": "Charlie", "age": "35"}'
]
df = spark.createDataFrame([(json_array,)], ["json_array"])
# Parse the JSON array using the schema
parsed_df = df.select(from_json(df.json_array, ArrayType(schema)).alias("parsed_array"))
# Extract the elements of the parsed array
parsed_df.selectExpr("parsed_array[0].name", "parsed_array[0].age").show()
```
This code defines a schema for a JSON object with `name` and `age` fields, creates a DataFrame with an example JSON array, parses the array using the schema, and then extracts the elements of the parsed array. The output of this code should be:
```
+------+---+
| name|age|
+------+---+
| Alice| 25|
+------+---+
```
pyspark list 转为json
可以使用Python内置的`json`模块将PySpark的list转换为JSON格式。下面是一个简单的示例:
```python
import json
from pyspark.sql.functions import collect_list
# 创建一个PySpark DataFrame
df = spark.createDataFrame([(1, 'a'), (2, 'b'), (1, 'c')], ['id', 'value'])
# 使用collect_list函数将value列转换为list
list_col = df.groupBy('id').agg(collect_list('value').alias('values')).collect()
# 将list转换为JSON格式
json_string = json.dumps([{'id': row.id, 'values': row.values} for row in list_col])
# 打印JSON字符串
print(json_string)
```
输出:
```
[{"id":1,"values":["a","c"]},{"id":2,"values":["b"]}]
```