05 query complex dynamic json data in snowflake

querying complex dynamic json data in snowflake is a powerful feature that allows you to work with semi-structured data directly alongside structured data. snowflake provides support for json, avro, parquet, and other semi-structured data formats.

in this tutorial, we will cover the following steps:

1. **creating a snowflake table for json data**
2. **loading json data into snowflake**
3. **querying json data with the `object`, `array`, and `flatten` functions**
4. **using common table expressions (ctes) for complex queries**
5. **using the `lateral` keyword for nested queries**

step 1: creating a snowflake table for json data

first, we need to create a table that will hold our json data. we can use a variant data type, which is designed to store semi-structured data in snowflake.

```sql
create or replace table json_data (
id int,
data variant
);
```

step 2: loading json data into snowflake

next, we will load some sample json data into our table. for this example, let's consider the following json data:

```json
[
{
"id": 1,
"name": "john doe",
"age": 30,
"address": {
"city": "new york",
"state": "ny"
},
"interests": ["music", "sports", "technology"]
},
{
"id": 2,
"name": "jane smith",
"age": 25,
"address": {
"city": "los angeles",
"state": "ca"
},
"interests": ["art", "travel"]
}
]
```

you can load this data using the `insert` command:

```sql
insert into json_data (id, data) values
(1, parse_json('{"name": "john doe", "age": 30, "address": {"city": "new york", "state": "ny"}, "interests": ["music", "sports", "technology"]}')),
(2, parse_json('{"name": "jane smith", "age": 25, "address": {"city": "los angeles", "state": "ca"}, "interests": ["art", "travel"]}'));
```

step 3: querying json data with functions

now that we have our data loaded, we can start querying it. snowflake provides s ...

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