Fragrantika News & Comments Datasets — Technical Specification
Snapshot date: 2026-10-08 (v5.18)
Source: fragrantica.com and 22 localized domains (fragrantica.de, fragrantica.ru, etc.)
Format: Apache Parquet (Zstandard compression)
Total combined size: ~1.56 GB on disk
This document specifies three datasets that complement the existing
Fragrantika perfume database (merged_database, brands_database_v2,
perfumers_database_v2, notes_database_v2 — already documented and sold
separately):
comments.parquet— user reviews on individual perfumesnews.parquet— editorial articles published on Fragrantikanews_comments.parquet— user comments under those articles
The cross-dataset relationships in §5 explain how to join these with the existing perfume/brand/perfumer DBs via primary keys.
1. Overview
| Dataset | Rows | Compressed Size | Distinct entities |
|---|---|---|---|
comments.parquet |
5,022,398 | 1.41 GB | 98,226 perfumes, 23 languages |
news.parquet |
25,780 articles | 114 MB | NID 1..26290 |
news_comments.parquet |
278,905 | 37 MB | 23,031 articles with comments |
All three datasets share the same identifier conventions used by the existing perfume/brand/perfumer databases:
- PID (
int32) — unique perfume identifier; matchesmerged_database.PID. - NID (
int32) — unique news article identifier (1..26290 range). - lang (
string) — ISO 639-1 language code identifying which Fragrantika domain the content was sourced from. Each domain hosts independent user-generated content (reviews are not translations of one another).
2. Dataset 1: comments.parquet
User-written reviews of individual perfumes, scraped across 23 localized Fragrantika domains. Each comment is a unique user review, not a translation or syndication.
2.1 Schema (8 fields)
| # | Field | Type | NULL? | Description |
|---|---|---|---|---|
| 1 | pid |
int32 |
NO | Foreign key → merged_database.PID. Identifies the perfume being reviewed. |
| 2 | lang |
string |
NO | Domain language (en, ru, de, …). 23 distinct values. |
| 3 | comment_id |
string |
NO | Globally unique deterministic ID, format {pid}_{lang}_{12hex} where 12hex is the first 12 hexadecimal characters of `sha1(author + " |
| 4 | author |
string |
NO | Username as displayed on Fragrantika. May contain Unicode (e.g. José, Søren, 李明). |
| 5 | date |
string |
NO | Date published as it appears on the page. Most rows: MM/DD/YY HH:MM (e.g., 04/11/26 10:05). Always present. |
| 6 | text |
large_string (64-bit offsets) |
NO | Review body. UTF-8, no HTML tags, paragraph breaks via \n. May contain emoji. Length range observed: 1 char (emoji-only) to ~120 KB. |
| 7 | avatar_url |
string |
NO | Full URL to the user's avatar image hosted on Fragrantika's CDN. Verified ~100% reachable. |
| 8 | gradient_class |
string |
NO | Fragrantika's CSS class for the user's color badge (e.g., tw-gradient-rose). 7 distinct values observed (tw-gradient-amber/emerald/orange/rose/sky/teal/violet). Useful for UI consistency if displaying. |
2.2 Volumetrics
- Total rows: 5,022,398
- Distinct PIDs covered: 98,226 — 98,214 of the 141,541 perfumes in
fragrances.csv(69.4%), plus 12 perfumes no longer in the catalogue; the remaining 43,327 perfumes have zero reviews - PID range: 1 — 144,189
- Languages: 23 (full list in §2.3)
2.3 Language distribution
| Lang | Code | Comments | Distinct PIDs |
|---|---|---|---|
| English | en |
1,913,238 | 81,616 (58% of perfumes) |
| Russian | ru |
938,870 | 55,094 |
| Portuguese (Brazilian) | pt |
283,681 | 23,258 |
| Spanish | es |
245,951 | 28,294 |
| Korean | ko |
215,074 | 11,707 |
| Turkish | tr |
192,846 | 11,820 |
| Japanese | ja |
188,341 | 10,846 |
| Polish | pl |
154,223 | 27,026 |
| Italian | it |
126,169 | 23,488 |
| Serbian | sr |
110,402 | 15,348 |
| Hungarian | hu |
109,532 | 11,568 |
| Swedish | sv |
108,006 | 11,166 |
| German | de |
101,525 | 15,749 |
| Hebrew | he |
83,236 | 10,257 |
| Ukrainian | uk |
53,175 | 16,523 |
| French | fr |
48,534 | 14,510 |
| Arabic | ar |
37,302 | 9,818 |
| Greek | el |
29,626 | 8,838 |
| Czech | cs |
24,435 | 3,468 |
| Chinese (Simplified) | zh |
16,017 | 4,585 |
| Dutch | nl |
15,442 | 6,682 |
| Romanian | ro |
14,632 | 6,648 |
| Mongolian | mn |
12,141 | 2,062 |
Each lang represents an independent set of user reviews from the
corresponding national Fragrantika domain. A user reviewing the same
perfume on fragrantica.com (en) and fragrantica.ru (ru) would write
two distinct reviews; both are included.
2.4 ID generation
comment_id is content-derived (sha1-based), giving three properties:
- Globally unique across all 5.0M rows (0 collisions in v5.18).
- Stable across re-scrapes: re-fetching the same comment yields the same ID. Useful for incremental updates and joining with downstream tables.
- Idempotent dedup key:
(nid, comment_id)andcomment_idalone are both safe primary keys.
3. Dataset 2: news.parquet
Editorial articles from fragrantica.com/news/ (English-only). Covers the
entire archive 2008-2026 (NID 1..26290), including both archived legacy
articles and modern editorial content.
3.1 Schema (16 fields)
| # | Field | Type | NULL? | Description |
|---|---|---|---|---|
| 1 | nid |
int32 |
NO | News article ID. Range 1..26290. |
| 2 | title |
string |
NO | Article title. Plain text, HTML entities decoded. |
| 3 | category |
string |
NO | Editorial category (e.g., New Fragrances, Fragrance Reviews, Interviews). 30+ distinct values. Top 10 in §3.4. |
| 4 | author |
string |
YES | Comma-separated list of author names (multi-author articles common). |
| 5 | description |
string |
YES | Short summary from <meta property="og:description">. Plain text. |
| 6 | text |
string |
NO | Full article body. Plain text, paragraph breaks via \n. Footer/byline blocks stripped. UTF-8. |
| 7 | text_html |
string |
NO | Article body with original HTML preserved — <p>, <a>, <img>, embedded videos. Useful for rendering or DOM-aware downstream processing. |
| 8 | main_image |
string |
YES | URL to the article's primary image (Fragrantika CDN). Verified reachable. |
| 9 | article_images |
string |
NO | JSON-encoded array of all image URLs in the article body. Use json.loads(field) → list[str]. Empty array '[]' if none. |
| 10 | url |
string |
NO | Canonical article URL (e.g., https://www.fragrantica.com/news/x-12345.html). |
| 11 | is_archived |
bool |
NO | True if article is in Fragrantika's legacy/archived corpus (older HTML template, often missing publication date — see §3.5). |
| 12 | related_pids |
string |
NO | JSON-encoded array of PIDs (as decimal strings) referenced in the article. Foreign key → merged_database.PID. 176 of 126,749 references (0.14%) point to perfumes no longer in the catalogue. |
| 13 | related_brands |
string |
NO | JSON-encoded array of brand names. Informational metadata; see §5.4 for canonical resolution. |
| 14 | related_perfumers |
string |
NO | JSON-encoded array of perfumer names with diacritics preserved (e.g., François Demachy, Carlos Benaïm). Informational; see §5.5. |
| 15 | comments_count |
int32 |
NO | Count of comments in news_comments.parquet matching this NID. |
| 16 | date_unix |
int64 |
NO | Publication time as Unix timestamp (seconds since epoch). 0 indicates the date is not extractable from the source HTML — see §3.5. |
3.2 Volumetrics
- Total rows: 25,780 articles
- NID range: 1 — 26,290 (510 NIDs in that range are absent from the source)
- Archived: 15,458 / 25,780 (60.0%)
- Non-archived: 10,322 / 25,780 (40.0%)
- With publication date (
date_unix > 0): 14,990 (58.1%)
3.3 List-fields format note
Four fields hold lists: article_images, related_pids, related_brands,
related_perfumers. All four are stored as JSON-encoded strings for
consistency. Use:
import json
images = json.loads(row['article_images']) # → list[str]
related_pids contains PID values as decimal strings (e.g., '704', not
the int 704). Cast as needed when joining.
3.4 Top categories
| Category | Articles | % |
|---|---|---|
| New Fragrances | 8,765 | 34.0% |
| Fragrance Reviews | 6,185 | 24.0% |
| Niche Perfumery | 2,616 | 10.2% |
| Art Books Events | 1,649 | 6.4% |
| Columns | 1,488 | 5.8% |
| Fragrant Horoscope | 875 | 3.4% |
| Fragrance News | 804 | 3.1% |
| Interviews | 692 | 2.7% |
| Vintages | 454 | 1.8% |
| Raw Materials | 397 | 1.5% |
Remaining 1,855 articles span 35 smaller categories.
3.5 Date coverage
date_unix == 0 for 10,790 articles (41.9%). Distribution by NID range:
| NID range | Articles | with date | % | archived % |
|---|---|---|---|---|
| 1 — 5,000 | 4,898 | 2 | 0.0% | 100% |
| 5,001 — 10,000 | 4,803 | 0 | 0.0% | 100% |
| 10,001 — 15,000 | 4,905 | 3,837 | 78.2% | 100% |
| 15,001 — 20,000 | 4,915 | 4,915 | 100% | 17.3% |
| 20,001 — 25,000 | 4,971 | 4,971 | 100% | 0% |
| 25,001 — 26,290 | 1,288 | 1,265 | 98.2% | 0% |
Of the 10,790 articles without date, 10,767 come from the archived legacy
template: 9,699 in NIDs 1–10,000 (all but 2 of the 9,701 there) and 1,068 in
NIDs 10,001–15,000 (the remaining 22% of that range — the other 78% have
recoverable visible-text dates). Fragrantika's old archived HTML does not
embed any date marker (no <time>, no <meta>, no visible date string)
for these. This is an upstream HTML limitation, not a parser issue.
The other 23 are the newest non-archived articles (23 of the 29 with NID 26,262 and above) whose
date was not captured at collection time — a gap on our side, not an upstream limitation.
Of the 10,322 non-archived articles, 10,299 have date_unix populated.
4. Dataset 3: news_comments.parquet
User comments under news articles. Pure UGC; same comment-card schema Fragrantika uses on perfume pages.
4.1 Schema (9 fields)
| # | Field | Type | NULL? | Description |
|---|---|---|---|---|
| 1 | nid |
int32 |
NO | Foreign key → news.parquet.nid (0% orphan rate). |
| 2 | comment_id |
string |
NO | Comment ID as Fragrantika assigns it (page-anchor format). Globally unique within parquet. |
| 3 | author |
string |
NO | Commenter username. |
| 4 | date |
string |
NO | Date as displayed on page (e.g., 04/11/26 10:05). |
| 5 | date_unix |
int64 |
NO | Parsed Unix timestamp. 100% populated (all rows have date_unix > 0). |
| 6 | text |
string |
NO | Comment body, plain text. |
| 7 | avatar_url |
string |
NO | Full URL to author avatar (Fragrantika CDN). |
| 8 | gradient |
string |
NO | CSS class for color badge (same scheme as comments.parquet.gradient_class). |
| 9 | is_reply |
bool |
NO | True if this comment is a reply to another comment (threaded discussion); False for root comments. 5.6% of rows are replies (15,604 / 278,905). |
4.2 Volumetrics
- Total rows: 278,905
- Distinct NIDs: 23,031 (89.3% of articles have at least one comment)
- Replies: 15,604 (5.6%)
- Average comments per article (in articles with comments): 12.1
5. Cross-dataset relationships
This section is the load-bearing piece for buyers integrating with the existing perfume/brand/perfumer DBs.
5.1 Diagram
┌────────────────────────────────────────────────────────┐
│ merged_database.csv (existing, 141,541 perfumes) │
│ ───────────────────── │
│ PID ←──────────────────────┐ │
│ Brand │ │
│ Name │ │
│ noses_f (perfumers) │ │
│ ...30 fields total │ │
└────────────────────────────────┼───────────────────────┘
│
┌────────────────┴───────────────┐
│ │
▼ ▼
┌──────────────────────┐ ┌──────────────────────┐
│ comments.parquet │ │ news.parquet │
│ ──────────────────── │ │ ──────────────────── │
│ pid ─────────────►│ │ related_pids ───────►│
│ lang (23 langs) │ │ related_brands │
│ comment_id (sha1) │ │ related_perfumers │
│ author/date/text │ │ nid ◄────┐ │
│ +avatar/gradient │ │ ...16 fields total │
└──────────────────────┘ └──────────┼───────────┘
│
│
┌──────────┴───────────┐
│ news_comments.parquet│
│ ──────────────────── │
│ nid ─────────────────│ FK → news.nid
│ comment_id │
│ author/date/text │
│ is_reply │
└──────────────────────┘
5.2 Linking comments to perfumes (PID)
Foreign key: comments.pid → merged_database.PID — every row joins except 62 reviews on 12 perfumes no longer in the catalogue.
-- All English reviews for the perfume "Mugler Angel" (PID 704):
SELECT c.author, c.date, c.text
FROM read_parquet('comments.parquet') c
JOIN read_csv('merged_database.csv', delim='⏸') m ON c.pid = m.PID
WHERE m.Brand = 'Mugler' AND m.Name = 'Angel' AND c.lang = 'en'
ORDER BY c.date DESC LIMIT 100;
import pyarrow.parquet as pq
import pyarrow.compute as pc
c = pq.read_table('comments.parquet')
angel_reviews = c.filter(pc.and_(pc.equal(c['pid'], 704),
pc.equal(c['lang'], 'en')))
5.3 Linking news to perfumes (related_pids)
Foreign key: news.related_pids → merged_database.PID — JSON-array
field; 126,749 references, of which 176 (0.14%) point to perfumes no longer in the catalogue.
-- All news mentioning Aventus (PID 9828):
SELECT nid, title, category, date_unix
FROM read_parquet('news.parquet')
WHERE list_contains(json_extract(related_pids, '$'), '9828');
import json
n = pq.read_table('news.parquet')
mentions_aventus = []
for i, rp in enumerate(n.column('related_pids').to_pylist()):
if rp and '9828' in json.loads(rp):
mentions_aventus.append(i)
5.4 Linking news to brands
news.related_brands is a JSON array of brand-name strings (informational).
Authoritative brand resolution for any news article uses the PID:
news.related_pids → merged_database.PID → merged_database.Brand
The related_brands field is provided as supplementary metadata. Approx.
12% of strings in related_brands will not match brands_database_v2.name
exactly because Fragrantika has renamed some brands over time
(e.g., Christian Dior → Dior, Annick Goutal → Goutal,
Paco Rabanne → Rabanne). The original captured name is preserved.
For canonical brand lookup, always join via related_pids:
SELECT DISTINCT m.Brand
FROM read_parquet('news.parquet') n
JOIN read_csv('merged_database.csv', delim='⏸') m
ON list_contains(json_extract(n.related_pids, '$'), CAST(m.PID AS VARCHAR))
WHERE n.nid = 17644;
5.5 Linking news to perfumers
Same pattern as brands. news.related_perfumers is a JSON array of perfumer-name
strings with diacritics preserved (e.g., François Demachy, Carlos Benaïm,
Cécile Zarokian — verified canonical post-fix).
Authoritative perfumer resolution uses PID:
news.related_pids → merged_database.PID → merged_database.noses_f
merged_database.noses_f contains the full list of perfumers per perfume in
the project's standard format. Approximately 11% of related_perfumers
strings will not exactly match perfumers_database_v2.name due to the
upstream perfumer DB not yet covering all names mentioned in news (e.g.,
Jean Claude Ellena ×191 mentions). Use the PID-join for guaranteed
matches.
5.6 Linking news_comments to articles (NID)
Foreign key: news_comments.nid → news.nid — 0% orphan rate.
-- All comments under article NID 17644:
SELECT author, date, text, is_reply
FROM read_parquet('news_comments.parquet')
WHERE nid = 17644
ORDER BY date_unix ASC;
5.7 Combined query examples
Q1. All news articles + their root comments mentioning Creed Aventus (PID 9828) in 2024:
SELECT n.nid, n.title, n.date_unix, nc.author, nc.text
FROM read_parquet('news.parquet') n
LEFT JOIN read_parquet('news_comments.parquet') nc ON n.nid = nc.nid
WHERE list_contains(json_extract(n.related_pids, '$'), '9828')
AND n.date_unix BETWEEN 1704067200 AND 1735689599 -- 2024
AND nc.is_reply = false
ORDER BY n.date_unix DESC, nc.date_unix ASC;
Q2. Top-10 most-reviewed perfumes by language:
SELECT lang, pid, COUNT(*) AS review_count
FROM read_parquet('comments.parquet')
GROUP BY lang, pid
QUALIFY ROW_NUMBER() OVER (PARTITION BY lang ORDER BY COUNT(*) DESC) <= 10;
Q3. Sentiment correlation between news articles and reviews — pairs of (news article, perfume reviewed in same time window):
SELECT n.nid, n.title, m.Brand, m.Name, COUNT(c.comment_id) AS reviews_in_30d
FROM read_parquet('news.parquet') n
JOIN read_csv('merged_database.csv', delim='⏸') m
ON list_contains(json_extract(n.related_pids, '$'), CAST(m.PID AS VARCHAR))
JOIN read_parquet('comments.parquet') c
ON c.pid = m.PID
WHERE n.date_unix > 0
AND c.date_unix BETWEEN n.date_unix AND n.date_unix + 2592000 -- 30 days
GROUP BY n.nid, n.title, m.Brand, m.Name;
6. Format specification
6.1 Storage
- Container: Apache Parquet 2.x
- Compression: Zstandard (
zstd) - Row groups:
comments.parquet— 5 row groupsnews.parquet— 1 row groupnews_comments.parquet— 1 row group
6.2 String types
PyArrow uses two string types:
string— backed by 32-bit offsets (per-array limit ~2 GB total).large_string— backed by 64-bit offsets (no practical size limit).
comments.parquet uses large_string for the text column (because the
combined corpus of 5.0M reviews exceeds the 32-bit offset limit). All
other string columns in all three datasets use string. Pandas
automatically converts both to its native object dtype on load — buyers
generally do not need to distinguish between the two types unless writing
custom Arrow code.
Exact field-level types are listed in the schema tables of §2.1, §3.1, §4.1.
6.3 Encoding
- Character encoding: UTF-8 throughout.
- Normalization: NFC where applicable; original Unicode codepoints preserved (including emoji).
- Newlines:
\nonly (Unix-style). No\r. - HTML entities: decoded (no
&,<, etc. in text fields). - Replacement chars (U+FFFD): zero — rare upstream-broken bytes were stripped, with the surrounding text preserved.
6.4 List fields (news.parquet)
Four columns store JSON-encoded arrays-as-strings:
article_images:list[str]of image URLsrelated_pids:list[str]of decimal-string PIDsrelated_brands:list[str]of brand namesrelated_perfumers:list[str]of perfumer names
Empty list is stored as the literal string '[]' (not NULL, not empty
string). This makes parsing branchless:
items = json.loads(row[field]) # always returns a list
7. Data quality
The datasets passed a multi-track validation audit (full report:
reports/data_quality/POST_FIX_VALIDATION.md). Summary:
| Check | Result |
|---|---|
| Duplicate rows by primary key (all 3 datasets) | 0 |
FK integrity (comments.pid → PID) |
62 rows on 12 perfumes no longer in the catalogue |
FK integrity (news.related_pids → PID) |
176 of 126,749 refs point to perfumes no longer in the catalogue |
FK integrity (news_comments.nid → nid) |
0 orphans |
comment_id global uniqueness (comments.parquet) |
0 collisions over 5.0M rows |
| HTML/CSS pollution in text fields | 0 |
| Cloudflare challenge pages in data | 0 |
| Mojibake / replacement char (U+FFFD) | 0 |
| Language attribution accuracy (langdetect on sample) | >95% per language |
news_comments.date_unix > 0 populated |
100% |
news.date_unix > 0 populated (non-archived) |
99.8% (10,299 / 10,322) |
7.1 Provenance
Data scraped via headless browser fingerprinting (chrome120 impersonation through curl_cffi) over a residential proxy network. Each page was individually fetched, parsed by a custom HTML parser, and post-processed through a content sanitization pipeline. Re-scrapes are idempotent thanks to deterministic comment IDs (§2.4).
8. Known limitations (transparent disclosure)
News articles without dates (10,790 / 25,780 = 41.9%). Fragrantika's archived HTML template does not embed any date marker (
<time>, meta tag, or visible string). For these articles,date_unixis0. The archived no-date subset is concentrated in NIDs 1–15,000: 9,699 of 9,701 archived articles in NIDs 1–10,000 and 1,068 of 4,905 in NIDs 10,001–15,000. (852 archived articles in NIDs 15,001–20,000 do have dates.) In addition, 23 of the 29 newest non-archived articles (NID 26,262 and above) were collected without their date; the remaining 10,299 of 10,322 non-archived articles are dated.related_brandsmatching gap (~12%). Fragrantika has renamed ~50 brands over the years (e.g.,Christian Dior → Dior); the captured name in news may be the older form, whilebrands_database_v2.csvcarries only the canonical (post-rename) name. Userelated_pidsfor authoritative brand resolution (§5.4).related_perfumersmatching gap (~11%). Some perfumer names referenced in news (e.g.,Jean Claude Ellena×191) are not yet in the companionperfumers_database_v2.csv. The names in news are diacritic-correct; the gap is in the reference DB coverage. Userelated_pids → merged_database.noses_ffor authoritative resolution (§5.5).Cross-language mirrored short comments (~0.014%). Approximately 650 short, identical-text comments appear in multiple languages (e.g., a "5/10" rating posted by the same author on multiple subdomains). These are real (Fragrantika's display behavior), not parser duplicates.
Comments PID coverage gap. 43,327 perfumes (30.6%) have zero comments in any language. In the May 2026 audit, checked against Fragrantika's
reviews_countfield, 99.8% of zero-comment perfumes truly had zero reviews on the platform. A targeted re-collection of the 73 PIDs flagged asreviews_count > 0yet missing comments recovered 68 of them (305 new comments added); the remaining 5 PIDs havereviews_count > 0in Fragrantika's metadata but the page returns no review HTML — treated as upstream metadata/page mismatch.
9. Loading examples
9.1 Python (PyArrow + Pandas)
import pyarrow.parquet as pq
import json
# Comments
comments = pq.read_table('comments.parquet')
df = comments.to_pandas()
print(df.head())
# News list-field unpack
news = pq.read_table('news.parquet').to_pandas()
news['related_pids'] = news['related_pids'].apply(json.loads)
news['related_brands'] = news['related_brands'].apply(json.loads)
9.2 DuckDB (zero-copy SQL on Parquet)
-- Direct query, no import needed
SELECT lang, COUNT(*) FROM 'comments.parquet' GROUP BY lang ORDER BY 2 DESC;
-- Multi-file join
SELECT n.title, COUNT(nc.comment_id) AS replies
FROM 'news.parquet' n
LEFT JOIN 'news_comments.parquet' nc ON n.nid = nc.nid AND nc.is_reply = true
GROUP BY n.nid, n.title HAVING replies > 10;
9.3 Polars
import polars as pl
df = pl.read_parquet('comments.parquet')
df.filter(pl.col('lang') == 'en').head()
10. Sample files
The samples/ directory contains three small Parquet files that
demonstrate the cross-dataset relationships using real production data:
| File | Rows | Content |
|---|---|---|
comments_sample.parquet |
25 | Reviews of 5 popular perfumes (Mugler Angel, Guerlain Shalimar, Creed Aventus, JPG Le Male, Dior Poison), each in 5 languages (en/ru/de/es/fr). |
news_sample.parquet |
20 | News articles that reference these 5 perfumes via related_pids. Diverse categories and archived/recent mix. |
news_comments_sample.parquet |
20 | Comments from 7 of the news articles in news_sample.parquet, mix of root and replies. |
The samples are produced by scripts/build_sales_samples.py and use the
identical Parquet schema and Zstandard compression as the production
files — buyers can verify their loading code against the samples before
committing to the full datasets.
10.1 Cross-link verification (using the samples)
import pyarrow.parquet as pq
import json
c = pq.read_table('samples/comments_sample.parquet')
n = pq.read_table('samples/news_sample.parquet')
nc = pq.read_table('samples/news_comments_sample.parquet')
sample_pids = set(c.column('pid').to_pylist())
print(f"Comment-sample PIDs: {sorted(sample_pids)}")
# {53, 218, 430, 704, 9828}
# Find news rows that reference these PIDs:
for i, rp in enumerate(n.column('related_pids').to_pylist()):
pids = set(int(p) for p in json.loads(rp) if p.isdigit())
if pids & sample_pids:
nid = n.column('nid').to_pylist()[i]
title = n.column('title').to_pylist()[i]
print(f" NID {nid} ({title[:60]}...) references PIDs {pids & sample_pids}")
# All news_comments NIDs are subset of news_sample NIDs:
sample_nids = set(n.column('nid').to_pylist())
nc_nids = set(nc.column('nid').to_pylist())
assert nc_nids <= sample_nids, "FK integrity holds in samples"
print(f"\nAll news_comments_sample NIDs link back to news_sample: {nc_nids <= sample_nids}")
Running this script on the supplied samples will print a verification trace and confirm relational integrity.
11. Versioning and updates
| Field | Value |
|---|---|
| Snapshot date | 2026-10-08 (v5.18) |
| Comments PID range | 1 — 144,189 |
| News NID range | 1 — 26,290 |
| Schema version | v1 (8 / 16 / 9 fields respectively) |
| Compression | zstd |
| Format | Parquet 2.x |
Updates to these datasets are produced as full snapshots; incremental diffs (per-PID / per-NID delta exports) are available on request.