Query JSON files using serverless SQL pool in Azure Synapse Analytics

In this article, you'll learn how to write a query using serverless SQL pool in Azure Synapse Analytics. The query's objective is to read JSON files using OPENROWSET.

  • Standard JSON files where multiple JSON documents are stored as a JSON array.
  • Line-delimited JSON files, where JSON documents are separated with new-line character. Common extensions for these types of files are jsonl, ldjson, and ndjson.

Read JSON documents

The easiest way to see to the content of your JSON file is to provide the file URL to the OPENROWSET function, specify csv FORMAT, and set values 0x0b for fieldterminator and fieldquote. If you need to read line-delimited JSON files, then this is enough. If you have classic JSON file, you would need to set values 0x0b for rowterminator. OPENROWSET function will parse JSON and return every document in the following format:

doc
{"date_rep":"2020-07-24","day":24,"month":7,"year":2020,"cases":3,"deaths":0,"geo_id":"AF"}
{"date_rep":"2020-07-25","day":25,"month":7,"year":2020,"cases":7,"deaths":0,"geo_id":"AF"}
{"date_rep":"2020-07-26","day":26,"month":7,"year":2020,"cases":4,"deaths":0,"geo_id":"AF"}
{"date_rep":"2020-07-27","day":27,"month":7,"year":2020,"cases":8,"deaths":0,"geo_id":"AF"}

If the file is publicly available, or if your Azure AD identity can access this file, you should see the content of the file using the query like the one shown in the following examples.

Read JSON files

The following sample query reads JSON and line-delimited JSON files, and returns every document as a separate row.

select top 10 *
from openrowset(
        bulk 'https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/ecdc_cases/latest/ecdc_cases.jsonl',
        format = 'csv',
        fieldterminator ='0x0b',
        fieldquote = '0x0b'
    ) with (doc nvarchar(max)) as rows
go
select top 10 *
from openrowset(
        bulk 'https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/ecdc_cases/latest/ecdc_cases.json',
        format = 'csv',
        fieldterminator ='0x0b',
        fieldquote = '0x0b',
        rowterminator = '0x0b' --> You need to override rowterminator to read classic JSON
    ) with (doc nvarchar(max)) as rows

The JSON document in the preceding sample query includes an array of objects. The query returns each object as a separate row in the result set. Make sure that you can access this file. If your file is protected with SAS key or custom identity, you would need to set up server level credential for sql login.

Data source usage

Previous example uses full path to the file. As an alternative, you can create an external data source with the location that points to the root folder of the storage, and use that data source and the relative path to the file in the OPENROWSET function:

create external data source covid
with ( location = 'https://pandemicdatalake.blob.core.windows.net/public/curated/covid-19/ecdc_cases' );
go
select top 10 *
from openrowset(
        bulk 'latest/ecdc_cases.jsonl',
        data_source = 'covid',
        format = 'csv',
        fieldterminator ='0x0b',
        fieldquote = '0x0b'
    ) with (doc nvarchar(max)) as rows
go
select top 10 *
from openrowset(
        bulk 'latest/ecdc_cases.json',
        data_source = 'covid',
        format = 'csv',
        fieldterminator ='0x0b',
        fieldquote = '0x0b',
        rowterminator = '0x0b' --> You need to override rowterminator to read classic JSON
    ) with (doc nvarchar(max)) as rows

If a data source is protected with SAS key or custom identity, you can configure data source with database scoped credential.

In the following sections, you can see how to query various types of JSON files.

Parse JSON documents

The queries in the previous examples return every JSON document as a single string in a separate row of the result set. You can use functions JSON_VALUE and OPENJSON to parse the values in JSON documents and return them as relational values, as it's shown in the following example:

date_rep cases geo_id
2020-07-24 3 AF
2020-07-25 7 AF
2020-07-26 4 AF
2020-07-27 8 AF

Sample JSON document

The query examples read json files containing documents with following structure:

{
    "date_rep":"2020-07-24",
    "day":24,"month":7,"year":2020,
    "cases":13,"deaths":0,
    "countries_and_territories":"Afghanistan",
    "geo_id":"AF",
    "country_territory_code":"AFG",
    "continent_exp":"Asia",
    "load_date":"2020-07-25 00:05:14",
    "iso_country":"AF"
}

Note

If these documents are stored as line-delimited JSON, you need to set FIELDTERMINATOR and FIELDQUOTE to 0x0b. If you have standard JSON format you need to set ROWTERMINATOR to 0x0b.

Query JSON files using JSON_VALUE

The query below shows you how to use JSON_VALUE to retrieve scalar values (date_rep, countries_and_territories, cases) from a JSON documents:

select
    JSON_VALUE(doc, '$.date_rep') AS date_reported,
    JSON_VALUE(doc, '$.countries_and_territories') AS country,
    CAST(JSON_VALUE(doc, '$.deaths') AS INT) as fatal,
    JSON_VALUE(doc, '$.cases') as cases,
    doc
from openrowset(
        bulk 'latest/ecdc_cases.jsonl',
        data_source = 'covid',
        format = 'csv',
        fieldterminator ='0x0b',
        fieldquote = '0x0b'
    ) with (doc nvarchar(max)) as rows
order by JSON_VALUE(doc, '$.geo_id') desc

Once you extract JSON properties from a JSON document, you can define column aliases and optionally cast the textual value to some type.

Query JSON files using OPENJSON

The following query uses OPENJSON. It will retrieve COVID statistics reported in Serbia:

select
    *
from openrowset(
        bulk 'latest/ecdc_cases.jsonl',
        data_source = 'covid',
        format = 'csv',
        fieldterminator ='0x0b',
        fieldquote = '0x0b'
    ) with (doc nvarchar(max)) as rows
    cross apply openjson (doc)
        with (  date_rep datetime2,
                cases int,
                fatal int '$.deaths',
                country varchar(100) '$.countries_and_territories')
where country = 'Serbia'
order by country, date_rep desc;

The results are functionally same as the results returned using the JSON_VALUE function. In some cases, OPENJSON might have advantage over JSON_VALUE:

  • In the WITH clause you can explicitly set the column aliases and the types for every property. You don't need to put the CAST function in every column in SELECT list.
  • OPENJSON might be faster if you are returning a large number of properties. If you are returning just 1-2 properties, the OPENJSON function might be overhead.
  • You must use the OPENJSON function if you need to parse the array from each document, and join it with the parent row.

Next steps

The next articles in this series will demonstrate how to: