Monday 9 July 2012

Nutch 2.0 is out (at last!)

Like pretty much any 2.0 release, Nutch 2.0 marks a radical change from the 1.x branch. I've mentioned 2.0 in previous posts but let's do a bit of history first. Nutch was initially started by Doug Cutting (Lucene's creator) and Mike Caffarella around 2002, then came the MapReduce paper from Google and in 2005 MapReduce was implemented as part of Nutch then became a sub project of Lucene at Apache. You know what happened to Hadoop after that : open source super-stardom, millions of dollars in investment, fierce competition between commercial distributions but also a myriad of related projects (HBase, ZooKeeper, Pig, Hive, Mahout etc...) with in the background the emergence of new concepts such as Big Data or NoSQL.

Meanwhile Nutch tagged along following the various releases of Hadoop but was based on the same architecture. It simply started relying on other projects more and more instead of implementing its own stuff, mainly Apache Tika (another offspring of Nutch) for parsing and extracting metadata from various document formats and Apache SOLR for indexing and searching documents. This made the code much lighter, easier to maintain and also up to date with all sorts of functionalities provided by these projects. However the way we stored and access data in Nutch remained the same since the beginning of Hadoop i.e. SequenceFiles and MapFiles.

Nutch 2.0 (a.k.a NutchGora) started in earnest 2 years ago when one of our clients decided to  invest in the development of a NoSQL-based version of Nutch. There had been a preliminary version called NutchBase developed by Dogacan Guney which was used as a basis except that instead of relying exclusively on HBase, we decided to implement our own Backend-Neutral-MapReduce-friendly-ORM which is now an Apache Top Level Project known as Apache GORA and serializes data with Apache AVRO. GORA provides us with a unified  access to various backends, NoSQL or not, an object-to-datastore mapping mechanism and utilities for MapReduce. This means that Nutch 2.0 can run on HBase, Cassandra, Accumulo or MySQL with just a few configuration files to modify.

One major change in 2.0 is that, instead of having a separation between the status of the URLs (crawlDB) separated from the data for these URLs (content and text in segments) and the webgraph (linkDB), we have a single table-like representation of the data where each entry contains everything we know about a URL, even the links that point to it or the various versions of its content (depending on the backend used). Not having separate segments is definitely good news. One of the side effects is that a fetch or parse step can be resumed. 

From a technical point of view this means that Nutch is not limited to the sequential processing of Hadoop data structures  but can operate at a more atomic level (GET, PUT). Most Nutch tasks are still MapReduce operations though but at least we can get the backends to filter the data and provide only what is needed for a specific task to the MapReduce operations.

The best example of this that I can think of is the update step in a Nutch crawl. Basically what this step does is to merge the information from a round of fetching with the rest of the CrawlDB, typically to change the status of the URLs we have fetched and add the new URLs we have discovered when parsing. With the 1.x branch this is done with a MapReduce operation which takes both the CrawlDB  and the segment as input, reduces on the URLs and updates the status of the CrawlDatum objects in the reduce step. All good. Except that as the crawlDB gets larger and larger, the time taken by the update step gets longer and longer up to a point where it ends up being the slowest part of the crawl. Think about a billion entries in the crawlDB and a single URL to update and you'll get the picture.

There are ways of alleviating this for 1.x (i.e. generate multiple segments in one go and update them with the crawldb at the same time) but the point is that with Nutch 2.0 the equivalent operation would be linear with the number of URLs modified, not the whole crawl dataset.

The change of paradigm between sequential datastructures to a table-like representation is a major change for Nutch which will certainly have many positive side-effects. Being the first release of 2.0, we can expect quite a few fixes to be needed and a massive overhaul of the documentation in the next months but the move seems to be positively welcomed by the Nutch community. Of course 1.x will continue to be the trunk for as long as necessary, i.e. until 2.0 is stable and has all the functionalities that  1.x has.

BTW my slides about 2.0 from last year's Berlin Buzzword are now here.

It is also a symbolic move, with Nutch being at the origin of many successful projects, it was about time it caught up with its famous offspring and the concepts which arose from it.


Wednesday 13 June 2012

What's new in Nutch 1.5

Apache Nutch 1.5 has been released last week. As with each release, this one contains a lot of changes and I will just comment on a few of them.

The main change is actually not in the list above and has not been documented in the Wiki yet. The binary version of Nutch (apache-nutch-1.5.bin.*) now contains the local runtime only, i.e. what you get in runtime/local when compiling the sources. This should make things a bit more straightforward for beginners as we've seen quite a bit of confusion on the mailing lists about which configuration files should be modified (root/conf vs runtime/local/conf). The src version of Nutch is unchanged and is what you'll need if you want to run Nutch on an existing Hadoop cluster. Of course, the runtime/local directory will be generated too from the source and you'll be able to run Nutch in local mode as well. In a nutshell, if you are not sure about what you're doing, want to use Nutch in local mode without a Hadoop cluster and/or do not need any custom plugins then the binary version is what you're after. I usually recommend to use the distributed version on a pseudo-distributed Hadoop cluster for production as the Hadoop web interfaces provide a wealth of useful information, not mentioning of course that you can have more than one mapper or reducer and harness the full potential of your server.

Apart from the usual dependency updates  (Hadoop 1.0.0, Tika 1.1), this release contains many improvements to the webgraph API, which is a better alternative than the default OPIC scoring in Nutch. In the future, it would be interesting to rely on a library such as Apache Giraph to compute the page ranks as it would simplify the code and also make it more efficient.

As mentioned in a previous post, the Nutch user and dev lists seem to indicate an increasing number of users, which is great. This also mean that we tend to see the same questions and issues coming over and over. One such question was about how to parse and index html metatags (see NUTCH-809) which I had contributed 2 years ago. The parse-metatags plugin is now available in the distribution and the steps are documented in the Wiki. Note that the parsing of the html metatags is not activated by default, this is something for the next release maybe.

An important and related change in Nutch 1.5 is NUTCH-1264 which provides a generic plugin for indexing metadata which is typically used alongside parsing plugins such as parse-metatags above and is based on configuration only. The metadata converted into fields for indexing can come from the crawldb, the parse metadata or the content metadata. More work is needed to delegate the indexing parts of existing plugins to it and this is likely to happen in the next release.

Again, Nutch 1.5 contains loads of improvements and you should definitely consider using it if you are on an older version. The next Nutch release will probably be 2.0 for which a RC is already available. Nutch 2.0, a.k.a NutchGora, is a complete redesign of Nutch based on Apache Gora and uses NoSQL datastores as backends instead of relying on the Hadoop data structures. We will have more releases from the 1.x branch as well as 2.x ones, until the latter gets stable and widely used by the community.

As usual, have a look, give it a try and contribute to Nutch if you can.

Friday 21 October 2011

Nutch hosting and monitoring

We now provide hosting and monitoring services for Apache Nutch.

For a fixed price, we will set up, run and monitor your Nutch crawler and report on its progress. The cost of the servers is included in the offer and their hardware specs are superior to what you get from Amazon EC2, without long term commitment as the service is on a monthly basis only.
The price depends on the size of the cluster as well as the complexity of the crawl.

If you use Nutch to feed documents to a seach engine, we can also monitor and host your SOLR instances for you!

Monday 26 September 2011

Visualising Nutch mailing-lists traffic

The graph below show the traffic on the Nutch dev and user mailing lists ( and from March 05 to August 11.

Traffic on Nutch mailing lists
(large size version of the graph here)

Unsurprisingly the traffic on the two lists follows similar trends with ups and downs and the user list globally more active than the dev list, apart from a period in 2005 (early Nutch development), a peak in July 2010 (discussions around Nutch 2.0 and refactoring of code) and the last few months. The figures for September are not complete but seem to confirm that Nutch is definitely back to a level of activity which has not been seen for the last 5 years.

Wednesday 6 July 2011

Crawler-Commons 0.1 released

As announced on various mailing-lists : 

The initial release of crawler-commons is available from :

The purpose of this project is to develop a set of reusable Java components that implement functionality common to any web crawler. These components would benefit from collaboration among various existing web crawler projects, and reduce duplication of effort. 

The current version contains resources for :
- parsing robots.txt
- parsing sitemaps
- URL analyzer which returns Top Level Domains
- a simple HttpFetcher

This release is available on Sonatype's OSS Nexus repository [] and should be available on Maven Central soon.

Please send your questions, comments or suggestions to
Doing the release was quite an interesting experience as I'd never done that before. This was the opportunity to have a closer look at ANT+Maven, how to publish artefacts and use Nexus etc... which I am sure will be useful at some point (Behemoth? GORA? Nutch?).

Now that crawler-commons is released we can start using it from Nutch, Bixo [see].

Sunday 12 June 2011

Nutch 1.3 released + BerlinBuzzwords presentation

Nutch 1.3 has been released and contains quite a few changes, some of which have been retrofitted from Nutch 2.0 in trunk.

The main modification is that Nutch now relies entirely on SOLR for indexing and searching and we removed our indexer based on Lucene as well as the search webapps (NUTCH-837). The dependencies are managed with Apache Ivy (NUTCH-821) and we've upgraded the versions of SOLR to 3.1 and Tika to 0.9. Another important change is that we have two separate runtime environments for local and deployed configurations (NUTCH-843). Nutch 1.3 contains a lot more improvements and bugfixes so if you use Nutch you should probably migrate to it.

The presentation I gave this week at BerlinBuzzwords is now available online and covered both 1.3 and 2.0, as well as an overview of Nutch. The conference itself was great and I met quite a few Nutch users and people who planned to use it as well as Doug Cutting, the creator of Nutch himself!

There are quite a few things planned for the next release(s) and also a large amount of work to do on the documentation which is a bit dated and patchy. Luckily some new committers have recently joined the project and seem keen to help with this.

Friday 27 May 2011

Parsing the Enron email dataset using Tika and Hadoop

In order to parse a large collection of emails, such as the Enron Email Dataset, we might choose to use Apache Hadoop, a scalable computing framework, and Apache Tika, a content analysis toolkit. This can be done easily with Behemoth, an open source platform for large scale document analysis developed by DigitalPebble. For more details of Behemoth, see the Behemoth Tutorial.

Using the August 21, 2009 version of the dataset, the first step is to use Behemoth's CorpusGenerator to create a corpus of BehemothDocuments from the Enron Dataset in HDFS. A BehemothDocument is the native object used by Behemoth. At ingest, it contains the original document, its content type and URL. After processing by a Behemoth module, it also contains the extracted text, additional metadata and annotations created about the document.

Once the dataset has been ingested, the next step is to use the Behemoth Tika module to create a Hadoop Map/Reduce job to extract the contents of the emails and metadata about them. Using Apache Tika 0.9, 5% of the documents fail to parse correctly. However using the latest version of Tika (Tika-1.0-snapshot revision 825923) only 0.2% documents fail.

One way to investigate why parsing is failing is by looking at the user logs generated within Hadoop, which contain details of the exceptions causing the failing documents. An alternative way is to write a custom reducer that sorts the exceptions thrown by Tika, with the exception stack being used as a key and a document URL as values. With Tika revision 825923, four exceptions are thrown, caused by two underlying problems: excessive line lengths of over 10,000 characters, the current default in the Tika mail parser, and malformed dates. The first problem can be solved by increasing the maximum line length in a MimeEntityConfig object and then modifying TikaProcessor to pass it into the ParseContext.

As for the second problem, currently the mail parser in Tika performs strict parsing, i.e. parsing a document fails when parsing a field fails. Tika-667 contains a contribution that makes it possible to turn off strict parsing, so some data can still be extracted from the emails with the malformed dates. This can also be configured via MimeEntityConfig. When these changes are incorporated, all documents are processed correctly.