Highly comparative time-series analysis with hctsa
  • Information about hctsa
    • Introduction
    • Getting started
    • Publications using hctsa
    • UMAP Projections
    • Related Time-Series Resources
    • List of included code files
    • FAQ
  • Installing and using hctsa
    • General advice and common pitfalls
    • Installing and setting up
      • Structure of the hctsa framework
      • Overview of an hctsa analysis
      • Compiling binaries
    • Running hctsa computations
      • Input files
      • Performing calculations
      • Inspecting errors
      • Working with hctsa files
    • Analyzing and visualizing results
      • Assigning group labels to data
      • Filtering and normalizing
      • Clustering rows and columns
      • Visualizing the data matrix
      • Plotting the time series
      • Low dimensional representation
      • Finding nearest neighbors
      • Investigating specific operations
      • Exploring classification accuracy
      • Finding informative features
      • Interpreting features
      • Comparing to existing features
      • Working with short time series
    • Working with a mySQL database
      • Setting up the mySQL database
      • The database structure
      • Populating the database with time series and operations
      • Adding time series
      • Retrieving from the database
      • Computing operations and writing back to the database
      • Cycling through computations using runscripts
      • Clearing or removing data
      • Retrieving data from the database
      • Error handling and maintenance
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  1. Installing and using hctsa
  2. Working with a mySQL database

Error handling and maintenance

In this section we describe how keywords and other types of metadata stored in the database can be manipulated, and how results of whole sets of operations and time series can be cleared or completely deleted from the database. These tasks are implemented as Matlab functions, and ensure that key database structures are maintained. Instead performing such tasks by acting directly on the database can cause inconsistencies and should be avoided.

Java heap space

Running out of java heap space throws the error java.lang.OutOfMemoryError, and usually happens when trying to retrieve a large set of time series/operations from the database. Matlab needs to keep the whole retrieval in memory, and has a hard limit on this. The java heap size can be increased in the Matlab preferences, under General Java Heap Memory.

PreviousRetrieving data from the database

Last updated 6 years ago

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