Colon sign operator for JSON

[Brad]

Hi,
I have a streaming source loading data to a raw table, which has a string type col (whose value is JSON) to hold all data. I want to use colon sign operator to get fields from the JSON string. Is this going to have some perf issues vs. I use a schema+from_json function?

Thanks

Brad

[Kaniz]

Hi @Brad, When dealing with JSON data in your streaming source, you have a couple of options for extracting fields.

Let’s explore both approaches:

1. Colon Sign Operator (:) for JSON Fields:

   • The colon sign operator allows you to directly access fields within a JSON string. For example, if your JSON string looks like this: {"name": "Alice", "age": 30}, you can extract the “name” field using json_column.name.
   • Pros:
     • Simplicity: It’s straightforward and concise.
     • No need to define a schema explicitly.
   • Cons:
     • Performance: Using the colon sign operator may have some performance overhead, especially when dealing with large datasets. Parsing the JSON string for each record can be computationally expensive.
     • Lack of type validation: The colon sign operator does not validate the data types of the extracted fields.
   • Use Case:
     • If you’re dealing with small datasets and simplicity is your priority, the colon sign operator can be convenient.

2. Schema + from_json Function:

   • In this approach, you define a schema for your JSON data and use the from_json function to parse the JSON string into a structured format.
   • Pros:
     • Performance: Defining a schema and using from_json can be more efficient, especially for large datasets. The schema provides type validation and optimization.
     • Type safety: You can enforce data types for each field.
   • Cons:
     • Slightly more verbose: You need to define the schema explicitly.
   • Use Case:
     • If performance and type safety are critical, especially for production-grade systems, using a schema and from_json is recommended.

If your dataset is small and you prioritize simplicity, the colon sign operator may suffice. However, for larger datasets or when type validation matters, defining a schema and using from_json ...¹².

[Brad]

Thanks Kaniz.

Yes, I did some testing. With some schema, I read the same data source and write the parsing results to diff tables. For 586K rows, the perf diff is 9sec vs. 37sec. For 2.3 million rows, 16sec vs. 133sec.