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szarnyasg committed Oct 22, 2024
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214 changes: 108 additions & 106 deletions _posts/2023-03-03-json.md
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Expand Up @@ -19,7 +19,7 @@ These functions are similar to the JSON functionality provided by other database
DuckDB uses [yyjson](https://github.com/ibireme/yyjson) internally to parse JSON, a high-performance JSON library written in ANSI C. Many thanks to the yyjson authors and contributors!

Besides these functions, DuckDB is now able to read JSON directly!
This is done by automatically detecting the types and column names, then converting the values within the JSON to DuckDB's vectors.
This is done by automatically detecting the types and column names, then converting the values within the JSON to DuckDB's vectors.
The automated schema detection dramatically simplifies working with JSON data and subsequent queries on DuckDB's vectors are significantly faster!

## Reading JSON Automatically with DuckDB
Expand Down Expand Up @@ -64,7 +64,7 @@ SELECT * FROM 'todos.json';
Now, finding out which user completed the most TODO items is as simple as:

```sql
SELECT userId, sum(completed::int) total_completed
SELECT userId, sum(completed::INTEGER) AS total_completed
FROM 'todos.json'
GROUP BY userId
ORDER BY total_completed DESC
Expand Down Expand Up @@ -111,7 +111,7 @@ This is specified with `nd` or the `lines` parameter:

```sql
SELECT * FROM read_ndjson_auto('todos2.json');
SELECT * FROM read_json_auto('todos2.json', lines='true');
SELECT * FROM read_json_auto('todos2.json', lines = 'true');
```

You can also set `lines='auto'` to auto-detect whether the JSON file is newline-delimited.
Expand All @@ -124,31 +124,30 @@ The first `json_format` is `'array_of_records'`, while the second is `'records'`
This can be specified like so:

```sql
SELECT * FROM read_json('todos.json', auto_detect=true, json_format='array_of_records');
SELECT * FROM read_json('todos2.json', auto_detect=true, json_format='records');
SELECT * FROM read_json('todos.json', format = 'array', records = true); -- ' json_format = 'array_of_records'
SELECT * FROM read_json('todos2.json', format = 'newline_delimited', records = true); -- json_format = 'records'
```

Other supported formats are `'values'` and `'array_of_values'`, which are similar to `'records'` and `'array_of_records'`.
However, with these formats, each 'record' is not required to be a JSON object but can also be a JSON array, string, or anything supported in JSON.

## Manual Schemas

What you may also have noticed is the `auto_detect` parameter.
This parameter tells DuckDB to infer the schema, i.e., determine the names and types of the returned columns.
DuckDB infers the schema, i.e., determines the names and types of the returned columns.
These can manually be specified like so:

```sql
SELECT * FROM read_json('todos.json',
columns={userId: 'INT', id: 'INT', title: 'VARCHAR', completed: 'BOOLEAN'},
json_format='array_of_records');
columns = {userId: 'INT', id: 'INT', title: 'VARCHAR', completed: 'BOOLEAN'},
json_format = 'array_of_records'); -- TODO: format // records
```

You don't have to specify all fields, just the ones you're interested in:

```sql
SELECT * FROM read_json('todos.json',
columns={userId: 'INT', completed: 'BOOLEAN'},
json_format='array_of_records');
columns = {userId: 'INT', completed: 'BOOLEAN'},
json_format = 'array_of_records');
```

Now that we know how to use the new DuckDB JSON table functions let's dive into some analytics!
Expand Down Expand Up @@ -191,9 +190,9 @@ To get a feel of what the data looks like, we run the following query:
```sql
SELECT json_group_structure(json)
FROM (
SELECT *
FROM read_ndjson_objects('gharchive_gz/*.json.gz')
LIMIT 2048
SELECT *
FROM read_ndjson_objects('gharchive_gz/*.json.gz')
LIMIT 2048
);
```

Expand Down Expand Up @@ -238,7 +237,8 @@ I've left `"payload"` out because it consists of deeply nested JSON, and its for
So, how many records are we dealing with exactly? Let's count it using DuckDB:

```sql
SELECT count(*) count FROM 'gharchive_gz/*.json.gz';
SELECT count(*) AS count
FROM 'gharchive_gz/*.json.gz';
```

| count |
Expand Down Expand Up @@ -356,12 +356,12 @@ This is more activity than normal because most of the DuckDB developers were bus
Now, let's see who was the most active:

```sql
SELECT actor.login, count(*) count
SELECT actor.login, count(*) AS count
FROM events
WHERE repo.name = 'duckdb/duckdb'
AND type = 'PullRequestEvent'
GROUP BY actor.login
ORDER BY count desc
ORDER BY count DESC
LIMIT 5;
```

Expand All @@ -383,29 +383,29 @@ We've ignored it because the contents of this field are different based on the t
We can see how they differ with the following query:

```sql
SELECT json_group_structure(payload) structure
SELECT json_group_structure(payload) AS structure
FROM (SELECT *
FROM read_json(
'gharchive_gz/*.json.gz',
columns={
id: 'BIGINT',
type: 'VARCHAR',
actor: 'STRUCT(id UBIGINT,
login VARCHAR,
display_login VARCHAR,
gravatar_id VARCHAR,
url VARCHAR,
avatar_url VARCHAR)',
repo: 'STRUCT(id UBIGINT, name VARCHAR, url VARCHAR)',
payload: 'JSON',
public: 'BOOLEAN',
created_at: 'TIMESTAMP',
org: 'STRUCT(id UBIGINT, login VARCHAR, gravatar_id VARCHAR, url VARCHAR, avatar_url VARCHAR)'
},
lines='true'
)
WHERE type = 'WatchEvent'
LIMIT 2048
FROM read_json(
'gharchive_gz/*.json.gz',
columns = {
id: 'BIGINT',
type: 'VARCHAR',
actor: 'STRUCT(id UBIGINT,
login VARCHAR,
display_login VARCHAR,
gravatar_id VARCHAR,
url VARCHAR,
avatar_url VARCHAR)',
repo: 'STRUCT(id UBIGINT, name VARCHAR, url VARCHAR)',
payload: 'JSON',
public: 'BOOLEAN',
created_at: 'TIMESTAMP',
org: 'STRUCT(id UBIGINT, login VARCHAR, gravatar_id VARCHAR, url VARCHAR, avatar_url VARCHAR)'
},
lines = 'true'
)
WHERE type = 'WatchEvent'
LIMIT 2048
);
```

Expand Down Expand Up @@ -491,47 +491,49 @@ Note that because we are not auto-detecting the schema, we have to supply `times
The key `"user"` must be surrounded by quotes because it is a reserved keyword in SQL:

```sql
CREATE TABLE pr_events as
SELECT *
FROM read_json(
'gharchive_gz/*.json.gz',
columns={
id: 'BIGINT',
type: 'VARCHAR',
actor: 'STRUCT(id UBIGINT,
login VARCHAR,
display_login VARCHAR,
gravatar_id VARCHAR,
url VARCHAR,
avatar_url VARCHAR)',
repo: 'STRUCT(id UBIGINT, name VARCHAR, url VARCHAR)',
payload: 'STRUCT(
action VARCHAR,
number UBIGINT,
pull_request STRUCT(
url VARCHAR,
id UBIGINT,
title VARCHAR,
"user" STRUCT(
login VARCHAR,
id UBIGINT
),
body VARCHAR,
created_at TIMESTAMP,
updated_at TIMESTAMP,
assignee STRUCT(login VARCHAR, id UBIGINT),
assignees STRUCT(login VARCHAR, id UBIGINT)[]
)
)',
public: 'BOOLEAN',
created_at: 'TIMESTAMP',
org: 'STRUCT(id UBIGINT, login VARCHAR, gravatar_id VARCHAR, url VARCHAR, avatar_url VARCHAR)'
},
json_format='records',
lines='true',
timestampformat='%Y-%m-%dT%H:%M:%SZ'
)
WHERE type = 'PullRequestEvent';
CREATE TABLE pr_events AS
SELECT *
FROM read_json(
'gharchive_gz/*.json.gz',
columns = {
id: 'BIGINT',
type: 'VARCHAR',
actor: 'STRUCT(
id UBIGINT,
login VARCHAR,
display_login VARCHAR,
gravatar_id VARCHAR,
url VARCHAR,
avatar_url VARCHAR
)',
repo: 'STRUCT(id UBIGINT, name VARCHAR, url VARCHAR)',
payload: 'STRUCT(
action VARCHAR,
number UBIGINT,
pull_request STRUCT(
url VARCHAR,
id UBIGINT,
title VARCHAR,
"user" STRUCT(
login VARCHAR,
id UBIGINT
),
body VARCHAR,
created_at TIMESTAMP,
updated_at TIMESTAMP,
assignee STRUCT(login VARCHAR, id UBIGINT),
assignees STRUCT(login VARCHAR, id UBIGINT)[]
)
)',
public: 'BOOLEAN',
created_at: 'TIMESTAMP',
org: 'STRUCT(id UBIGINT, login VARCHAR, gravatar_id VARCHAR, url VARCHAR, avatar_url VARCHAR)'
},
json_format = 'records',
lines = 'true',
timestampformat = '%Y-%m-%dT%H:%M:%SZ'
)
WHERE type = 'PullRequestEvent';
```

This query completes in around 36s with an on-disk database (resulting size is 478MB) and 9s with an in-memory database.
Expand Down Expand Up @@ -561,13 +563,13 @@ We can check who was assigned the most:

```sql
WITH assignees AS (
SELECT payload.pull_request.assignee.login assignee
FROM pr_events
UNION ALL
SELECT unnest(payload.pull_request.assignees).login assignee
FROM pr_events
SELECT payload.pull_request.assignee.login assignee
FROM pr_events
UNION ALL
SELECT unnest(payload.pull_request.assignees).login assignee
FROM pr_events
)
SELECT assignee, count(*) count
SELECT assignee, count(*) AS count
FROM assignees
WHERE assignee NOT NULL
GROUP BY assignee
Expand Down Expand Up @@ -596,25 +598,25 @@ If you don't want to specify the schema of a field, you can set the type as `'JS
CREATE TABLE pr_events AS
SELECT *
FROM read_json(
'gharchive_gz/*.json.gz',
columns={
id: 'BIGINT',
type: 'VARCHAR',
actor: 'STRUCT(id UBIGINT,
login VARCHAR,
display_login VARCHAR,
gravatar_id VARCHAR,
url VARCHAR,
avatar_url VARCHAR)',
repo: 'STRUCT(id UBIGINT, name VARCHAR, url VARCHAR)',
payload: 'JSON',
public: 'BOOLEAN',
created_at: 'TIMESTAMP',
org: 'STRUCT(id UBIGINT, login VARCHAR, gravatar_id VARCHAR, url VARCHAR, avatar_url VARCHAR)'
},
json_format='records',
lines='true',
timestampformat='%Y-%m-%dT%H:%M:%SZ'
'gharchive_gz/*.json.gz',
columns = {
id: 'BIGINT',
type: 'VARCHAR',
actor: 'STRUCT(id UBIGINT,
login VARCHAR,
display_login VARCHAR,
gravatar_id VARCHAR,
url VARCHAR,
avatar_url VARCHAR)',
repo: 'STRUCT(id UBIGINT, name VARCHAR, url VARCHAR)',
payload: 'JSON',
public: 'BOOLEAN',
created_at: 'TIMESTAMP',
org: 'STRUCT(id UBIGINT, login VARCHAR, gravatar_id VARCHAR, url VARCHAR, avatar_url VARCHAR)'
},
json_format = 'records',
lines = 'true',
timestampformat = '%Y-%m-%dT%H:%M:%SZ'
)
WHERE type = 'PullRequestEvent';
```
Expand All @@ -623,7 +625,7 @@ This will load the `"payload"` field as a JSON string, and we can use DuckDB's J
For example:

```sql
SELECT DISTINCT payload->>'action' AS action, count(*) count
SELECT DISTINCT payload->>'action' AS action, count(*) AS count
FROM pr_events
GROUP BY action
ORDER BY count DESC;
Expand Down
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