Use a system.properties file to configure the system. This is loaded statically by MainClass or ProcessMainClass. Update the property names to be more consistent, and update the documentations to reflect the changes.
Add a toggle for saving the WARC data generated by the search engine's crawler. Normally this is discarded, but for debugging or archival purposes, retaining it may be of interest.
The warc files are concatenated into larger archives, up to about 1 GB each.
An index is also created containing filenames, domain names, offsets and sizes
to help navigate these larger archives.
The warc data is saved in a directory warc/ under the crawl data storage.
The changeset also makes the control service responsible for flyway migrations. This helps reduce the number of places the database configuration needs to be spread out. These automatic migrations can be disabled with -DdisableFlyway=true.
The commit also adds curl to the docker container, to enable docker health checks and interdependencies.
The new converter logic assumes that the crawl data is ordered where the domain record comes first, and then a sequence of document records. This is true for the new parquet format, but not for the old zstd/gson format.
To make the new converter compatible with the old format, a specialized reader is introduced that scans for the domain record before running through the sequence of document records; and presenting them in the new order.
This is slower than just reading the file beginning to end, so in order to retain performance when this ordering isn't necessary, a CompatibilityLevel flag is added to CrawledDomainReader, permitting the caller to decide how compatible the data needs to be.
Down the line when all the old data is purged, this should be removed, as it amounts to technical debt.
The URI query string is now URL encoded in the WarcProtocolReconstructor. This change ensures proper encoding of special characters as per the standard URL encoding rules and improves URL validity during the crawling process.
Guava's hashers are a bit allocation hungry, and a big driver of GC churn in the crawler. This switches to the modified Murmur hash function used throughout Marginalia.
A number of crawl jobs get stuck at about 300 documents, or just under. This seems to be because we fail to increase the crawl limit, which is based on MAX(200, 1.25 x GOOD_URLS) with a 1.5x modifier applied upon a recrawl. GOOD_URLS is based on how many documents successfully process, which is typically fairly small. Switching to KNOWN_URLS should let this grow faster.
The SQL query in the DbCrawlSpecProvider class has been updated; 'GOOD_URLS' has been replaced with 'KNOWN_URLS'. This update ensures the correct data is selected from the DOMAIN_METADATA table.
The floor is also increased to 250 from 200.
Make some temporary modifications to the CrawledDocument model to support both a "big string" style headers field like in the old formats, and explicit fields as in the new formats. This is a bit awkward to deal with, but it's a necessity until we migrate off the old formats entirely.
The commit also adds a few tests to this logic.
This variable had a very confusing name, and was dangerously easy to use in the wrong place with the result of getting something that only works as expected half the time.
Ideally this class needs an overhaul, the assumptions it makes about domain names aren't great.
There really is no fantastic place to put this logic, but we need to remove entries with an X-Robots-Tags header where that header indicates it doesn't want to be crawled by Marginalia.
This information is then propagated to the parquet file as a boolean.
For documents that are copied from the reference, use whatever value we last saw. This isn't 100% deterministic and may result in false negatives, but permits websites that used cookies but have stopped to repent and have the change reflect in the search engine more quickly.
This commit includes mostly exception handling, error propagation, a few bug fixes and minor changes to log formatting. The CrawlDelayTimer, HTTP 429 responses and IOException responses are now more accurately handled.
A non-standard WarcXEntityRefused WARC record has also been introduced, essentially acting as a rejected 'response' with different semantics.
Besides these, several existing features have been refined, such as URL encoding, crawl depth incrementing and usage of Content-Length headers.
This commit further cleans up the warc->parquet conversion. It fixes issues with redirect handling in WarcRecorder, adds support information about redirects and errors due to probe failure.
It also refactors the fetch result, body extraction and content type abstractions.
This commit cleans up the warc->parquet conversion. Records with a http status other than 200 are now included.
The commit also fixes a bug where the robots.txt parser would be fed the full HTTP response (and choke), instead of the body.
The DocumentBodyExtractor code has also been cleaned up, and now offers a way of just getting the byte[] representation for later processing, as conversion to and from strings is a bit wasteful.
This commit is in a pretty rough state. It refactors the crawler fairly significantly to offer better separation of concerns. It replaces the zstd compressed json files used to store crawl data with WARC files entirely, and the converter is modified to be able to consume this data. This works, -ish.
There appears to be some bug relating to reading robots.txt, and the X-Robots-Tag header is no longer processed either.
A problem is that the WARC files are a bit too large. It will probably be likely to introduce a new format to store the crawl data long term, something like parquet; and use WARCs for intermediate storage to enable the crawler to be restarted without needing a recrawl.
At this stage, the crawler will use the WARCs to resume a crawl if it terminates incorrectly.
This is a WIP commit, since the warc files are not fully incorporated into the work flow, they are deleted after the domain is crawled.
The commit also includes fairly invasive refactoring of the crawler classes, to accomplish better separation of concerns.
In this commit, GeoIP-related classes are refactored and relocated to a common library as they are shared across multiple services.
The crawler is refactored to enable the GeoIpBlocklist to use the new GeoIpDictionary as the base of its decisions.
The converter is modified ot query this data to add a geoip:-keyword to documents to permit limiting a search to the country of the hosting server.
The commit also adds due BY-SA attribution in the search engine footer for the source of the IP geolocation data.
Partially hook in the WarcRecorder into the crawler process. So far it's not read, but should record the crawled documents.
The WarcRecorder and HttpFetcher classes were also refactored and broken apart to be easier to reason about.
This is a first step of using WARC as an intermediate flight recorder style step in the crawler, ultimately aimed at being able to resume crawls if the crawler is restarted. This component is currently not hooked into anything.
The OkHttp3 client wrapper class 'WarcRecordingFetcherClient' was implemented for web archiving. This allows for the recording of HTTP requests and responses. New classes were introduced, 'WarcDigestBuilder', 'IpInterceptingNetworkInterceptor', and 'WarcProtocolReconstructor'.
The JWarc dependency was added to the build.gradle file, and relevant unit tests were also introduced. Some HttpFetcher-adjacent structural changes were also done for better organization.
This functionality needs to be accessed by the WarcSideloader, which is in the converter. The resultant microlibrary is tiny, but I think in this case it's justifiable.
Wrapping these exceptions in a try-catch and logging them with slf4j will ensure they end up in the process logs.
The way it worked using the default exception handler, they'd print on console (which nothing captures!), leading to a very annoying debugging experience.
This turned out to be very difficult to do in small isolated steps.
* Design overhaul of the control gui using bootstrap
* Move the actors out of control-service into to a new executor-service, that can be run on multiple nodes
* Add node-affinity to message queue
