🕷️ Crawler Inspector

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Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 129 (from laksa104)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa129.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, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://willperkins.org/4221old/markov.html\')), getAhrefsUnparsedNoserviceFromURL(\'https://willperkins.org/4221old/markov.html\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/willperkins.org\/4221old\/markov.html","crawl_time":1774461038,"first_indexed_time":1720640725,"http_code":200,"src_unparsed":"org,willperkins!\/4221old\/markov.html s443","src_root_hash":"7807022309337797529","history_drop_reason":null,"meta_title":"Math 4221: Markov Chains","meta_descriptions":[],"attrs_boilerpipe_text":"Instructor Will Perkins  wperkins3@math.gatech.edu  Office: Skiles 017   Office Hours: Wednesday 10 am - 12pm, or by appointment  ","attrs_markdown":"# Markov Chains\n### [MATH 4221](https:\/\/willperkins.org\/4221old\/index.html)\n### Fall 2012\n#### Skiles 254\n#### M \/ W \/ F, 12:05 - 12:55 pm\n\nInstructor\n\n[Will Perkins](http:\/\/people.math.gatech.edu\/~wperkins3\/%20)\n\n*wperkins3@math.gatech.edu*\n\nOffice: Skiles 017\n\nOffice Hours: Wednesday 10 am - 12pm, or by appointment\n\nTopics\n\n- Sections: 6.1 - 6.6, 6.14\n- Definitions:\n  1. Markov Chain\n  2. Homogeneous Markov Chain\n  3. Transition Matrix\n  4. n-step Transition Matrix\n  5. Recurrent State\n  6. Transient State\n  7. Null and positive recurrent\n  8. Periodic\n  9. Intercommunicating States\n  10. Closed\n  11. Irreducible\n  12. Stationary Distribution\n  13. Recurrence Time\n  14. Reversible\n  15. Total Variation Distance (3 definitions)\n  16. Mixing Time\n  17. Coupling of Two Markov Chains\n  18. Random Walk on a Graph\n- Theorems: 6.1.5, 6.1.8, 6.2.3, 6.2.4, 6.2.5, 6.2.9, 6.3.2, 6.3.3, 6.3.4, 6.3.5, 6.4.3, 6.4.6, 6.4.17, 6.5.4, 6.6.1, 6.14.9, Coupling Collison Time Bound on Mixing Time,\n- Sample Questions:\n  1. What is the mixing time for a random walk on the complete graph with self loops?\n  2. Give upper and lower bounds for the mixing time of a random walk on two complete graphs of size n connected by a single edge.\n  3. Can a single Markov Chain have more than one stationary distribution? Why or why not?\n  4. Consider a two state MC with states A, B. p(A,A) =1\/2, p(A, B) =1\/2. P(B,B) =1\/4, P(B,A) =3\/4. What is the stationary distribution? What are the eigenvalues of the adjacency matrix?\n  5. Is a branching process a reversible Markov Chain? How about SRW?\n  6. Decompose the state space of the branching process MC.\n  7. Prove that 3d random walk is transient.\n  8. Prove that 2d random walk is null recurrent.\n  9. What is the stationary distribution of the random walk on the complete bipartite graph where the left partition has n vertices, the right 2n, and at each step there is probability 1\/2 of remaining in the current state.\n  10. Give a graph whose random walk has period 3.\n  11. Give a Markov chain whose state space is not irreducible.\n  12. Give a Markov chain whose state space can be partitioned into two closed sets of states.\n  13. Consider m balls lying in n bins. At each step we pick a ball at random out of a bin, and throw it into a bin chosen uniformly at random. Is this a Markov Chain? What is the state space? Clasify the chain. What is the stationary distribution? Give upper and lower bounds for its mixing time.","attrs_readable_markdown":null,"meta_canonical":null}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📄

INDEXABLE

✅

CRAWLED

26 days 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`	0.9 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://willperkins.org/4221old/markov.html
Last Crawled	2026-03-25 17:50:38 (26 days ago)
First Indexed	2024-07-10 19:45:25 (1 year ago)
HTTP Status Code	200
Meta Title	Math 4221: Markov Chains
Meta Description	null
Meta Canonical	null
Boilerpipe Text	Instructor Will Perkins wperkins3@math.gatech.edu Office: Skiles 017 Office Hours: Wednesday 10 am - 12pm, or by appointment
Markdown	# Markov Chains ### [MATH 4221](https://willperkins.org/4221old/index.html) ### Fall 2012 #### Skiles 254 #### M / W / F, 12:05 - 12:55 pm Instructor [Will Perkins](http://people.math.gatech.edu/~wperkins3/%20) wperkins3@math.gatech.edu Office: Skiles 017 Office Hours: Wednesday 10 am - 12pm, or by appointment Topics - Sections: 6.1 - 6.6, 6.14 - Definitions: 1. Markov Chain 2. Homogeneous Markov Chain 3. Transition Matrix 4. n-step Transition Matrix 5. Recurrent State 6. Transient State 7. Null and positive recurrent 8. Periodic 9. Intercommunicating States 10. Closed 11. Irreducible 12. Stationary Distribution 13. Recurrence Time 14. Reversible 15. Total Variation Distance (3 definitions) 16. Mixing Time 17. Coupling of Two Markov Chains 18. Random Walk on a Graph - Theorems: 6.1.5, 6.1.8, 6.2.3, 6.2.4, 6.2.5, 6.2.9, 6.3.2, 6.3.3, 6.3.4, 6.3.5, 6.4.3, 6.4.6, 6.4.17, 6.5.4, 6.6.1, 6.14.9, Coupling Collison Time Bound on Mixing Time, - Sample Questions: 1. What is the mixing time for a random walk on the complete graph with self loops? 2. Give upper and lower bounds for the mixing time of a random walk on two complete graphs of size n connected by a single edge. 3. Can a single Markov Chain have more than one stationary distribution? Why or why not? 4. Consider a two state MC with states A, B. p(A,A) =1/2, p(A, B) =1/2. P(B,B) =1/4, P(B,A) =3/4. What is the stationary distribution? What are the eigenvalues of the adjacency matrix? 5. Is a branching process a reversible Markov Chain? How about SRW? 6. Decompose the state space of the branching process MC. 7. Prove that 3d random walk is transient. 8. Prove that 2d random walk is null recurrent. 9. What is the stationary distribution of the random walk on the complete bipartite graph where the left partition has n vertices, the right 2n, and at each step there is probability 1/2 of remaining in the current state. 10. Give a graph whose random walk has period 3. 11. Give a Markov chain whose state space is not irreducible. 12. Give a Markov chain whose state space can be partitioned into two closed sets of states. 13. Consider m balls lying in n bins. At each step we pick a ball at random out of a bin, and throw it into a bin chosen uniformly at random. Is this a Markov Chain? What is the state space? Clasify the chain. What is the stationary distribution? Give upper and lower bounds for its mixing time.
Readable Markdown	null
Shard	129 (laksa)
Root Hash	7807022309337797529
Unparsed URL	org,willperkins!/4221old/markov.html s443