🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 169 (from laksa148)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa169.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, meta_canonical AS meta_canonical, ml_categories_json AS ml_categories_json, ml_types_json AS ml_types_json, ml_intent_types_json AS ml_intent_types_json, meta_language AS meta_language, attrs_author AS attrs_author, ifNull(toUnixTimestamp(attrs_publish_time), 0) AS attrs_publish_time, ifNull(toUnixTimestamp(attrs_original_publish_time), 0) AS attrs_original_publish_time, ifNull(attrs_is_republished, 0) AS attrs_is_republished, ifNull(attrs_nr_words, 0) AS attrs_nr_words, ifNull(attrs_boilerpipe_nr_words, 0) AS attrs_boilerpipe_nr_words, ifNull(body_ext_links_number, 0) AS body_ext_links_number, ifNull(body_int_links_number, 0) AS body_int_links_number, ifNull(meta_nofollow, 0) AS meta_nofollow, ifNull(meta_noarchive, 0) AS meta_noarchive, ifNull(props_was_rendered, 0) AS props_was_rendered, ifNull(src_redirect, \'\') AS src_redirect, ifNull(download_time_msec, 0) AS download_time_msec, ifNull(download_ttfb_msec, 0) AS download_ttfb_msec, ifNull(download_size, 0) AS download_size FROM crawler3.page_info_local FINAL PREWHERE int_partition_id = 68 AND (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://builtin.com/data-science/ols-regression\')), getAhrefsUnparsedNoserviceFromURL(\'https://builtin.com/data-science/ols-regression\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/builtin.com\/data-science\/ols-regression","crawl_time":1777262755,"first_indexed_time":1676402502,"http_code":200,"src_unparsed":"com,builtin!\/data-science\/ols-regression s443","src_root_hash":"7607033694470393769","history_drop_reason":null,"meta_title":"Understanding Ordinary Least Squares (OLS) Regression | Built In","meta_descriptions":["Ordinary least squares (OLS) regression is an optimization technique applied to linear regression models to minimize the sum of squared differences between observed and predicted values. It obtains a straight line as close as possible to data points."],"meta_canonical":null,"ml_categories_json":"{\"\/Science\":784,\"\/Science\/Mathematics\":600,\"\/Science\/Mathematics\/Statistics\":578,\"\/Computers_and_Electronics\":217,\"\/Computers_and_Electronics\/Software\":186,\"\/Computers_and_Electronics\/Software\/Educational_Software\":146}","ml_types_json":"{\"\/Article\":998,\"\/Article\/Tutorial_or_Guide\":886}","ml_intent_types_json":"{\"Informational\":999}","meta_language":"en","attrs_author":"Valentina Alto","attrs_publish_time":0,"attrs_original_publish_time":1676402502,"attrs_is_republished":0,"attrs_nr_words":"1729","attrs_boilerpipe_nr_words":"1417","body_ext_links_number":8,"body_int_links_number":66,"meta_nofollow":0,"meta_noarchive":0,"props_was_rendered":1,"src_redirect":"","download_time_msec":339,"download_ttfb_msec":338,"download_size":14625}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📍

LOCATION

Host 169 · Partition 68

laksa169

7607033694470393769

📄

INDEXABLE

✅

CRAWLED

1 month ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	1.2 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Page Details

Property

Value

URL

https://builtin.com/data-science/ols-regression

Last Crawled

2026-04-27 04:05:55 (1 month ago)

First Indexed

2023-02-14 19:21:42 (3 years ago)

HTTP Status Code

200

Content

Meta Title

Understanding Ordinary Least Squares (OLS) Regression | Built In

Meta Description

Ordinary least squares (OLS) regression is an optimization technique applied to linear regression models to minimize the sum of squared differences between observed and predicted values. It obtains a straight line as close as possible to data points.

Meta Canonical

null

Boilerpipe Text

heavy column, fetched on demand

Markdown

heavy column, fetched on demand

Readable Markdown

heavy column, fetched on demand

ML Classification

ML Categories

/Science		78.4%
/Science/Mathematics		60.0%
/Science/Mathematics/Statistics		57.8%
/Computers_and_Electronics		21.7%
/Computers_and_Electronics/Software		18.6%
/Computers_and_Electronics/Software/Educational_Software		14.6%

Raw JSON

{
    "/Science": 784,
    "/Science/Mathematics": 600,
    "/Science/Mathematics/Statistics": 578,
    "/Computers_and_Electronics": 217,
    "/Computers_and_Electronics/Software": 186,
    "/Computers_and_Electronics/Software/Educational_Software": 146
}

ML Page Types

/Article		99.8%
/Article/Tutorial_or_Guide		88.6%

Raw JSON

{
    "/Article": 998,
    "/Article/Tutorial_or_Guide": 886
}

ML Intent Types

Informational

99.9%

Raw JSON

{
    "Informational": 999
}

Content Metadata

Language

Author

Valentina Alto

Publish Time

not set

Original Publish Time

2023-02-14 19:21:42 (3 years ago)

Republished

Word Count (Total)

1,729

Word Count (Content)

1,417

Links

External Links

Internal Links

Technical SEO

Meta Nofollow

Meta Noarchive

JS Rendered

Yes

Redirect Target

null

Performance

Download Time (ms)

339

TTFB (ms)

338

Download Size (bytes)

14,625

Location

Host ID

169 (laksa169)

Partition ID

Root Hash

7607033694470393769

Unparsed URL

com,builtin!/data-science/ols-regression s443