> ## Documentation Index
> Fetch the complete documentation index at: https://jmail.world/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# DuckDB / SQL
> Query Parquet files directly over HTTP with SQL
[DuckDB](https://duckdb.org/) can query Parquet files directly over HTTP with zero download or setup. This is the fastest way to explore the data interactively.
## Setup
Install DuckDB, then query directly:
```bash theme={null}
duckdb
```
```sql theme={null}
SELECT sender, COUNT(*) as n
FROM read_parquet('https://data.jmail.world/v1/emails-slim.parquet')
GROUP BY sender ORDER BY n DESC LIMIT 20;
```
## Example Queries
### 
Count emails by sender
```sql theme={null}
SELECT sender, COUNT(*) as n
FROM read_parquet('https://data.jmail.world/v1/emails-slim.parquet')
GROUP BY sender ORDER BY n DESC LIMIT 20;
```
### Emails sent by Epstein
```sql theme={null}
SELECT subject, sent_at, to_recipients
FROM read_parquet('https://data.jmail.world/v1/emails-slim.parquet')
WHERE epstein_is_sender = true
ORDER BY sent_at DESC LIMIT 20;
```
### 
Search documents
```sql theme={null}
SELECT original_filename, document_description, page_count
FROM read_parquet('https://data.jmail.world/v1/documents.parquet')
WHERE document_description ILIKE '%flight%'
LIMIT 20;
```
### 
Join photos with people
```sql theme={null}
SELECT p.name, COUNT(*) as appearances
FROM read_parquet('https://data.jmail.world/v1/photo_faces.parquet') pf
JOIN read_parquet('https://data.jmail.world/v1/people.parquet') p
ON pf.person_id = p.id
GROUP BY p.name ORDER BY appearances DESC;
```
### Star counts by entity type
```sql theme={null}
SELECT entity_type, SUM(count) as total_stars
FROM read_parquet('https://data.jmail.world/v1/star_counts.parquet')
GROUP BY entity_type ORDER BY total_stars DESC;
```
## Using with Polars
[Polars](https://pola.rs/) can also read Parquet over HTTP:
```python theme={null}
import polars as pl
df = pl.read_parquet("https://data.jmail.world/v1/emails-slim.parquet")
print(df.group_by("sender").len().sort("len", descending=True).head(20))
```
## Using with Pandas
```python theme={null}
import pandas as pd
df = pd.read_parquet("https://data.jmail.world/v1/emails-slim.parquet")
print(df.groupby("sender").size().sort_values(ascending=False).head(20))
```