CosmoHub: Interactive exploration and distribution of astronomical data on Hadoop

P. Tallada*, J. Carretero, J. Casals, C. Acosta-Silva, S. Serrano, M. Caubet, F. J. Castander, E. César, M. Crocce, M. Delfino, M. Eriksen, P. Fosalba, E. Gaztañaga, G. Merino, C. Neissner, N. Tonello

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


We present CosmoHub (, a web application based on Hadoop to perform interactive exploration and distribution of massive cosmological datasets. Recent Cosmology seeks to unveil the nature of both dark matter and dark energy mapping the large-scale structure of the Universe, through the analysis of massive amounts of astronomical data, progressively increasing during the last (and future) decades with the digitization and automation of the experimental techniques. CosmoHub, hosted and developed at the Port d'Informació Científica (PIC), provides support to a worldwide community of scientists, without requiring the end user to know any Structured Query Language (SQL). It is serving data of several large international collaborations such as the Euclid space mission, the Dark Energy Survey (DES), the Physics of the Accelerating Universe Survey (PAUS) and the Marenostrum Institut de Ciències de l'Espai (MICE) numerical simulations. While originally developed as a PostgreSQL relational database web frontend, this work describes the current version of CosmoHub, built on top of Apache Hive, which facilitates scalable reading, writing and managing huge datasets. As CosmoHub's datasets are seldomly modified, Hive it is a better fit. Over 60 TiB of cataloged information and 50×109 astronomical objects can be interactively explored using an integrated visualization tool which includes 1D histogram and 2D heatmap plots. In our current implementation, online exploration of datasets of 109 objects can be done in a timescale of tens of seconds. Users can also download customized subsets of data in standard formats generated in few minutes.

Original languageEnglish
Article number100391
Number of pages19
JournalAstronomy and Computing
Early online date31 May 2020
Publication statusPublished - 1 Jul 2020


  • Apache Hadoop
  • Apache Hive
  • ASDF
  • Data distribution
  • Data exploration
  • FITS

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