Using Queues in Web Crawling and Analysis Infrastructure

Message oriented middleware (MOM) is a key technology for implementing a custom pipeline and analyzing unstructured data. The pipeline for going from crawling web pages to part of speech tagging (PoST) and beyond is long. It requires a variety of processes which are implemented in several different programming languages and operating systems. For example, boilerpipe is an excellent Java library for extracting main text content while PoSTs libraries, like NLTK or FreeLing, are implemented in Python.

One might be tempted to integrate different technologies using web services but web services alone have many weak points. If the pipeline has ten processes and, for example, the last one fails, then the intermediate processes can be lost if they are not persisted. There must be a higher level mechanism in place to resume the pipeline processing. MOMs ensure message persistence until a consumer acknowledges that a specific process has finished.

There are a lot of MOMs to choose from, including commercial and free open source variants. Some features are present in almost all of them while others are not. Contention management is an important feature if you are dealing, as is likely, with a high ratio of messages produced to messages consumed at any one time. For example, a web crawler can fetch web pages at an incredibly high speed while processes like content extraction take longer. Running a message queue without contention management under these circumstances will exhaust the machine’s memory.

While MOMs are important for uniting heterogeneous technologies, the different processes must also know which queues to utilize to consume the input and produce the output for the next phases. A new wave of frameworks like NServiceBusResque, Celery, and Octobot has emerged to handle this.

In conclusion, MOMs help to connect heterogeneous technologies and bring robustness, and are very useful in the context of unstructured information like text analysis. Many MOMs are available, but there is not a single one with a complete feature set. However some of these features can be supplied by frameworks such as NServiceBus, Resque, Celery, and Octobot.

See Also

  1. Esoteric Queue Scheduling Disciplines
  2. Persisting Native Python Queues
  3. Adding Acknowledgement Semantics to a Persistent Queue


  1. Message Queues vs Web Services
  2. Message Queue Evaluation Notes
  3. The Hadoop Map-Reduce Capacity Scheduler
  4. Contention Management in the WSA
  5. Message Queuing Architectures