DBpedia 2016-10 Usage report (as of 2020-10-01)

Virtuoso Universal Server Linked Data Deployment
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DBpedia 2016-10 Usage Report as of 1 October 2020

A periodic report on the DBpedia SPARQL endpoint and associated Linked Data deployment

Copyright (C) 2020 OpenLink Software

Introduction

This document shows some of the statistics collected between July 2017 and September 2020, spanning more than 3 year of logs from the DBpedia web service operated by OpenLink Software at http://dbpedia.org/sparql/ .

The log files used to prepare this document include data from the following DBpedia release:

Infrastructure

The DBpedia service consists of:

  • two or more Virtuoso Universal Server Instances — facilitating Linked Data Deployment including providing a SPARQL endpoint delivering RDF data in a variety of document formats subject to content-negotiation.
  • a Reverse Proxy Server — which redirects client requests to an available Virtuoso instance and caches the results in case another client repeats the same request within a specified timeframe
  • a physical computer — hosted in OpenLink Software’s datacenter

Currently the DBpedia service is hosted on two virtual machines running CentOS 6, each using 8 Intel Xeon E5–2630 2.30 GHz cores with 200 GB SSD and 64GB memory, hosting Virtuoso 7.2 Enterprise Edition with the Column Store Module.

Rate and Connection limits

To maintain equitable access to the DBpedia service for everyone, OpenLink limits connections by rate and concurrent connection, limiting disruption by faulty or misbehaving applications.

Current limit rates are:

  • Connection limit of 50 parallel connections per IP address . This number is fairly high to permit multiple clients in networks using Network Address Translation (NAT) to appear as one network IP. Without the use of tracking cookies, it is impossible to distinguish between machines inside a NAT network, and for privacy and legal reasons, OpenLink has decided not to use such cookies at this point in time.
  • Rate limit of 100 requests per second per IP address , with an initial burst of 120 requests.

As part of monitoring the DBpedia service, OpenLink performs frequent traffic analysis to make sure the service is running smoothly.

Ideally, applications should be written to check the HTTP status code of each request, and in case of a 503 (Service Unavailable) or 429 (Too Many Requests) code, perform a 1–2 second sleep before retrying the request.

OpenLink may alter these parameters at any time to make sure the service remains reachable to the general public.

In case of misuse, OpenLink may temporarily block an offender’s IP address from accessing the DBpedia service. This temporary ban will be automatically lifted once such a blocked IP address refrains from making any request to the DBpedia service for at least 5 minutes.

Configured Virtuoso limits on the DBpedia endpoint

The Virtuoso configuration for the DBpedia endpoint includes:

  • Query Execution Timeout of 120 seconds. This is the query solution preparation threshold. If the timeout stops execution before the solution is complete — i.e., if the solution is partial — this is indicated to the query client via HTTP response headers.
  • Maximum SPARQL query solution (aka result set) size of 10,000 rows. This is the maximum number of solution rows (for SELECT queries) or triple/quad statements (for CONSTRUCT or DESCRIBE queries) returned per query-solution-retrieval round-trip.

Virtuoso “Anytime Query” Functionality

The “Anytime Query” is a core feature of Virtuoso that enables it to handle the challenges inherent in providing a publicly accessible interface for ad-hoc querying at Web scale. This feature allows an application compliant with the SPARQL- and HTTP-protocol to issue long-running and/or large-solution queries, for which finding the complete solution would exceed configured query timeout and/or result set limits, and rather than being rebuffed with no solution, to receive partial solutions conforming to those thresholds. Further, this feature enables the use of LIMIT and OFFSET (typically combined with ORDER BY and/or GROUP BY) to create windows (also known as sliding windows or cursors ) to iterate through the complete query solution without being adversely affected by inserts or deletions.

Note: Even while paging through a partial query solution, Virtuoso continues to work towards a complete solution in the background.

Custom HTTP headers

As the W3C SPARQL standard currently does not specify an authoritative status code or header response to report a partial result set, OpenLink Software has opted to have Virtuoso return a status code of 200 to denote a successful request and add a custom header to the result to indicate that the result was limited to what could be returned within the settings enforced by the server.

If full execution of the query would return more than the configured maximum number of rows, the X-SPARQL-MaxRows line is added, as shown below:

HTTP/1.1 200 OK
Date: Tue, 1 Jan 2018 12:00:00 GMT
Content-Type: text/html; charset=UTF-8
Content-Length: 1427536
Connection: keep-alive
Vary: Accept-Encoding
Server: Virtuoso/07.20.3224 (Linux) i686-generic-linux-glibc212-64 VDB
X-SPARQL-default-graph: http://dbpedia.org
X-SPARQL-MaxRows: 10000
Expires: Tue, 07 Jan 2018 12:00:00 GMT
Cache-Control: max-age=604800
Access-Control-Allow-Origin: *
Access-Control-Allow-Credentials: true
Access-Control-Allow-Methods: HEAD, GET, POST, OPTIONS
Access-Control-Allow-Headers: DNT,X-CustomHeader,Keep-Alive,User-Agent,X-Requested-With,If-Modified-Since,Cache-Control,Content-Type,Accept-Encoding
Accept-Ranges: bytes

If the AnyTime Query timeout is reached, several headers are added:

HTTP/1.1 200 OK
Date: Tue, 01 Jan 2018 12:00:00 GMT
Content-Type: text/html; charset=UTF-8
Content-Length: 80
Connection: keep-alive
Server: Virtuoso/07.20.3224 (Linux) i686-generic-linux-glibc212-64 VDB
X-SPARQL-default-graph: http://dbpedia.org
X-SQL-State: S1TAT
X-SQL-Message: RC...: Returning incomplete results, query interrupted by result timeout. Activity: 7 rnd 64.87M seq 0 same seg 1 same pg 0 same par 0 disk 0 spec disk 0B / 0 mess
X-Exec-Milliseconds: 30000
X-Exec-DB-Activity: 7 rnd 64.87M seq 0 same seg 1 same pg 0 same par 0 disk 0 spec disk 0B / 0 messages 0 fork
Expires: Tue, 07 Jan 2018 12:00:00 GMT
Cache-Control: max-age=604800
Access-Control-Allow-Origin: *
Access-Control-Allow-Credentials: true
Access-Control-Allow-Methods: HEAD, GET, POST, OPTIONS
Access-Control-Allow-Headers: DNT,X-CustomHeader,Keep-Alive,User-Agent,X-Requested-With,If-Modified-Since,Cache-Control,Content-Type,Accept-Encoding
Accept-Ranges: bytes

Hosting Independent DBpedia Instances

The restrictions described above may impair some complex analytical queries. Users who frequently encounter these limits are advised to:

HTTP logs

The HTTP server log files used in this report exclude traffic generated by:

  • IP addresses that were temporarily rate-limited after their burst period
  • IP addresses that were banned after misuse
  • applications, spiders, and other crawlers that were blocked after frequently hitting the rate-limiter or which generally claimed too many resources

The system uses a combination of firewall rules and Access Control Lists (ACLs) to quickly drop such connections, so legitimate users of the DBpedia service can continue to connect and execute queries.

To save time, these dropped connections are not recorded in the log files.

The data for this document was extracted from reports generated by Webalizer v2.21.

HTTP Usage Historical Overview

The first table shows the average numbers of Visits and Hits per day during the time each DBpedia dataset was was live on the OpenLink Virtuoso SPARQL Query Editor endpoint.

DBpedia From Until Visits per day Hits per day Total Hits
3.3 2009-06-30 2009-11-05 9,602 733,811 94,661,592
3.4 2009-11-06 2010-04-07 11,100 1,212,549 185,519,930
3.5 2010-04-08 2011-01-17 16,381 1,122,612 282,898,279
3.6 2011-01-18 2011-06-30 19,288 1,328,355 219,178,587
3.7 2011-07-01 2012-06-19 23,408 2,052,660 594,338,675
3.8 2012-06-20 2013-09-19 16,614 2,925,335 570,440,410
3.9 2013-09-20 2014-09-02 22,026 3,035,428 1,062,399,840
2014 2014-09-03 2015-07-05 27,927 3,423,490 1,051,011,401
2015-04 2015-07-06 2016-03-31 24,689 3,516,936 953,089,788
2015-10 2016-04-01 2016-10-13 110,745 6,581,217 1,263,593,686
2016-04 2016-10-14 2017-07-03 231,735 7,646,447 2,003,369,014
2016-10 2017-07-04 present 257,618 7,348,400 8,699,117,044

Hits

The following graph shows the average number of hits (or requests) per day that were made to the DBpedia service during each of the releases.

image
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Coinciding with the DBpedia 2015–10 release on April 1 2016 there has been a dramatic increase in the number of Hits, which we attribute to the work in promoting DBpedia via the Community meetings as well as communication with various partners in the Linked Data community to increase back-links.

Visits

The following graph shows the average number of unique visits per day made to the DBpedia service during each of the datasets.

image
image679Ă—351 20.3 KB

Similarly to the hits graph above we even more clearly see a huge increase in visits since the DBpedia 2015–10 release.

We consider multiple hits (or requests) by the same client with less than 30 minutes between two requests to comprise a single “visit”. A gap of more than 30 minutes between requests starts a second “visit”.

While web crawlers (like Google, DuckDuckGo, Bing, and Yahoo) normally do not make many distinct visits, projects hosted on Google’s UserContents, Amazon, and other cloud services do contribute to the number of visits.

OpenLink may analyze the visitor data from these various services separately in a future analytics document.

Linked Data Deployment

When talking about DBpedia, we normally refer to the SPARQL endpoint; however DBpedia offers also Linked Data Deployment via its /resource , /page , and /data endpoints as well as via applications like the OpenLink Faceted browser on /fct and /describe .

The next graph shows the percentage of the total number of hits in a given time period that can be attributed to the /sparql endpoint. If we look at the historical data from 2014–09 onward, we can see the requests to /sparql were about 60.16% of the total number of hits.

If we focus on the last 12 months, we can see a slightly lower average of 48.10%, as shown in the following graph:

image
image728Ă—328 48.1 KB

This means that around 50% of traffic uses Linked Data constructions to view information available through DBpedia. To put this into perspective, that means that of the average of 7.2 million hits to the endpoint on a given day, 3.6 million hits are Linked Data Deployment hits.

HTTP Usage Overview per month

The following table shows the information on visits, sited and hits for
each month between 7 July 2017 and 30 September 2020.

Month Avg visits/day Avg hits/day Avg sites/day Total visits/month Total hits/month
Sep 20 215,275 5,182,890 8,960 6,458,273 155,486,717
Aug 20 220,123 4,084,772 7,976 6,823,828 126,627,951
Jul 20 236,908 4,295,223 7,173 7,344,157 133,151,920
Jun 20 209,731 3,953,945 6,950 6,291,954 118,618,378
May 20 317,421 5,424,694 7,566 9,840,080 168,165,516
Apr 20 256,302 6,697,775 9,737 7,689,076 200,933,269
Mar 20 297,540 6,665,140 9,187 9,223,766 206,619,369
Feb 20 220,700 7,255,914 10,175 6,400,322 210,421,529
Jan 20 171,482 4,287,020 18,216 5,315,968 132,897,632
Dec 19 199,133 6,080,577 10,426 6,173,149 188,497,899
Nov 19 212,631 6,426,288 7,876 6,378,934 192,788,645
Oct 19 283,127 10,830,337 6,566 8,776,942 335,740,455
Sep 19 230,720 7,837,989 7,348 6,921,614 235,139,683
Aug 19 263,489 9,425,091 6,075 8,168,164 292,177,848
Jul 19 342,808 9,460,654 6,932 10,627,065 293,280,303
Jun 19 306,472 10,333,570 6,510 9,194,176 310,007,118
May 19 270,442 7,939,766 6,588 8,383,727 246,132,759
Apr 19 265,194 7,694,194 6,805 7,955,848 230,825,849
Mar 19 292,466 8,761,301 7,760 9,066,473 271,600,335
Feb 19 289,675 9,393,051 6,877 8,110,926 263,005,448
Jan 19 259,233 8,764,751 6,990 8,036,241 271,707,300
Dec 18 268,824 6,707,095 6,588 8,333,548 207,919,949
Nov 18 209,250 8,088,759 6,526 6,277,501 242,662,799
Oct 18 217,562 8,336,568 5,843 6,744,450 258,433,633
Sep 18 190,524 5,426,150 5,224 5,715,735 162,784,511
Aug 18 193,607 4,548,647 4,539 6,001,824 141,008,065
Jul 18 256,854 8,202,696 6,240 7,962,494 254,283,601
Jun 18 164,804 4,184,158 4,479 4,944,146 125,524,761
May 18 208,519 6,126,606 5,021 6,464,117 189,924,812
Apr 18 197,363 4,613,147 5,637 5,920,910 138,394,420
Mar 18 259,410 7,975,823 5,490 8,041,731 247,250,543
Feb 18 311,558 14,890,083 6,300 8,723,634 416,922,336
Jan 18 316,331 10,577,535 7,815 9,806,275 327,903,592
Dec 17 342,571 10,632,253 12,560 10,619,719 329,599,863
Nov 17 357,392 9,194,890 6,779 10,721,776 275,846,718
Oct 17 361,476 7,675,818 6,005 11,205,783 237,950,359
Sep 17 352,603 6,947,742 5,470 10,578,109 208,432,279
Aug 17 259,332 6,086,300 5,077 8,039,309 188,675,319
Jul 17 218,240 5,578,398 4,521 6,328,970 161,773,561
Sum 305,610,714 8,699,117,044
Average 257,618 7,348,400 7,251 7,836,172 223,054,283
Stdev 54,061 2,358,558 2,496 1,669,030 69,529,929
Median 259,233 7,255,914 6,779 7,962,494 210,421,529
Min 164,804 3,953,945 4,479 4,944,146 118,618,378
Max 361,476 14,890,083 18,216 11,205,783 416,922,336
Days 1185 1185

Note: There is a bias when taking an average from a set of averages;
however, calculating the actual average as (sum of all hits) Ă· (number
of days in dataset) , or 8,699,117,044 Ă· 1185, we get 7,341,027
. Compared to the 7,348,400 average-of-averages from the table above,
this is a 0.11% difference, which we consider insignificant.

The above table is also available as a Google Sheet.

Hits

The following graph shows the average number of hits (or requests) per day over the last year.

image
image686Ă—328 48.3 KB

Visits

The following graph shows the average number of visits per day.

image
image686Ă—328 61.4 KB

Average number of Hits per Visit

Dividing one by the other, we get hits per visit over the last year:

image
image674Ă—328 51.9 KB

Sites

The last graph shows the number of unique IP addresses that made requests to the DBpedia service.

image
image686Ă—328 47.3 KB

Since it is not possible to track individual IP addresses behind a NAT firewall, these figures should not be taken as absolute.

Links

Previous Reports

Some of the statistics in this document were previously published as part of:

1 Like
2

Hi,

I am very interested in your report. So how do I download the dbpedia query logs?

Thank you