Enhancing organization and maintenance of big data with Apache Solr in IBM WebSphere Commerce deployments
Grigel, Rudolf (2015)
Grigel, Rudolf
Jyväskylän ammattikorkeakoulu
2015
Creative Commons Attribution-NonCommercial 3.0 Unported
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2015060512588
https://urn.fi/URN:NBN:fi:amk-2015060512588
Tiivistelmä
The main objective of this thesis was to enhance the organization and maintenance of big
data with Apache Solr in IBM WebSphere Commerce deployments. This objective can be
split into several subtasks: reorganization of data, fast and optimised exporting and
importing, efficient update and cleanup operations.
E-Commerce is a fast growing and frequently changing environment. There is a constant
flow of data that is rapidly growing larger and larger every day which is becoming an
serious problem in the current process of data handling. Apache Solr is an enterprise
search platform used by IBM WebSphereCommerce. It is a fast indexing engine that can
handle large amounts of data with proper configuration, data organization and custom
extensions.
This thesis results in extensions for Apache Solr programmed in Solr's Java API. Other
expected results of this thesis are data organization rules and recommendations that can
help with the current big data situation with Apache Solr in IBM WebSphere Commerce.
Testing and evaluation of the results are an important part of this thesis and tests are run
with currently deployed IBM WebSphere Commerce systems and data that comes from
these eCommerce systems.
data with Apache Solr in IBM WebSphere Commerce deployments. This objective can be
split into several subtasks: reorganization of data, fast and optimised exporting and
importing, efficient update and cleanup operations.
E-Commerce is a fast growing and frequently changing environment. There is a constant
flow of data that is rapidly growing larger and larger every day which is becoming an
serious problem in the current process of data handling. Apache Solr is an enterprise
search platform used by IBM WebSphereCommerce. It is a fast indexing engine that can
handle large amounts of data with proper configuration, data organization and custom
extensions.
This thesis results in extensions for Apache Solr programmed in Solr's Java API. Other
expected results of this thesis are data organization rules and recommendations that can
help with the current big data situation with Apache Solr in IBM WebSphere Commerce.
Testing and evaluation of the results are an important part of this thesis and tests are run
with currently deployed IBM WebSphere Commerce systems and data that comes from
these eCommerce systems.