[Optimization 4/4] H3 spatial joins in pqg_demo.ipynb

[rdhyee]

Priority: 8 (lowest — tutorial enhancement)

Context

The PQG demo notebook shows multi-hop graph traversals for spatial queries. With H3 columns pre-computed in the wide format, we can demonstrate spatial aggregation without traversal — a significant simplification.

Data Files on R2

File	URL	Size
Wide + H3	https://pub-a18234d962364c22a50c787b7ca09fa5.r2.dev/isamples_202601_wide_h3.parquet	292 MB
Facet summaries	https://pub-a18234d962364c22a50c787b7ca09fa5.r2.dev/isamples_202601_facet_summaries.parquet	2 KB

File to Modify

examples/basic/pqg_demo.ipynb

Current Behavior

Demonstrates multi-hop traversals for spatial queries:

Sample → produced_by → SamplingEvent → sample_location → GeospatialCoordLocation

This is correct for the narrow (graph) format but verbose.

Desired Changes

1. Add "Wide format shortcut" section

After the existing graph traversal section, add a new section showing the equivalent query using the wide format with H3:

import duckdb

con = duckdb.connect()
wide_h3_url = "https://pub-a18234d962364c22a50c787b7ca09fa5.r2.dev/isamples_202601_wide_h3.parquet"

# "What materials are found in the Bay Area?"
# With H3: single query, no traversal needed
bay_area_samples = con.sql(f"""
 WITH bay_area AS (
 SELECT DISTINCT h3_res6
 FROM read_parquet('{wide_h3_url}')
 WHERE otype = 'MaterialSampleRecord'
 AND latitude BETWEEN 37.0 AND 38.5 AND longitude BETWEEN -123.0 AND -121.5
 )
 SELECT
 c.label as material,
 COUNT(*) as count
 FROM read_parquet('{wide_h3_url}') w
 JOIN read_parquet('{wide_h3_url}') c
 ON c.row_id = ANY(w.p__has_material_category)
 WHERE w.h3_res6 IN (SELECT h3_res6 FROM bay_area)
 AND w.otype = 'MaterialSampleRecord'
 AND c.otype = 'IdentifiedConcept'
 GROUP BY c.label
 ORDER BY count DESC
""").df()

2. Add comparison table

Show when to use graph traversal (narrow) vs H3 shortcut (wide):

Use Case	Best Format	Why
"Show me the full provenance chain"	Narrow (graph)	Need explicit edge traversal
"What materials are in this area?"	Wide + H3	Single query, no joins
"How many samples per source per region?"	Wide + H3	Aggregation with spatial filter

3. Performance comparison

Time the graph traversal vs the H3 shortcut for the same spatial query.

Acceptance Criteria

• New section demonstrating H3 spatial shortcut
• Side-by-side with existing graph traversal
• Comparison table: when to use which approach
• Performance timing for both approaches
• Notebook runs end-to-end