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Managing Large Data Sets
James McNally, CLA
(Re-) Introduce Myself
Twitter - @JamesMc86
www.wiresmithtech.com/blog
www.jamesmcnally.co.uk (old)
Why LabVIEW is Special
Leading the way on dealing with live data:
● 1GB/s + Hardware Interface Support
● GPU Processing, Intel MKL Based Palettes
● Inherent Parallelism
DATAFLOW
Today
➔Life of Data
➔System Design
➔Techniques to Consider
Data Must Be...
Challenging at high speed or in large volumes.
Captured Analysed Moved RetrievedStored
The Battle Ground
Real
World
CPU
RAM
HDD
NAS
or
Network Services
TB-PB128M-16GB
GB-TB
50-500MB/s
0.1-1GB/s
<10GB/s
1-120MB/s
System Design Example
AE Sensor x4
up to 500kHz
DAQ Card
1MS/s
AE Sensor x4
up to 500kHz
DAQ Card
1MS/s
x8 Total
CPU
32MS/s
Requirements
- All events captured.
- 30 second circular buffer to capture and
show data from before the event.
- Data for all channels must be stored, even
if the event is on one channel.
Some Considerations
➔Data Formats
○ e.g. DAQmx TDMS Files
➔Data Compression
➔Appropriate Rates
○ E.G. Reduction for Displays
➔64 Bit LabVIEW
Algorithmic Complexity
Understand how well your algorithms scale.
DVRs
DVR - Throw and Catch
Guarantees no data copies in transit,
whatever method is used.
DVR - Nested Arrays
➔Reduces contiguous memory requirements.
➔Allows ‘odd’ shaped data allocations
Databases - Wildly Generalised!
➔Great for ‘random’ retrieval
➔Good for providing data to other languages
esp. web based
➔Design may be non-trivial
➔Bad for waveform data (traditionally)
➔Platform considerations for interfacing
‘Database’ Technology to Consider
➔Traditional Relational Databases
○ MySQL, PostgreSQL, SQL Server
○ Widely used and good online support
➔Datafinder
○ No database to see, indexes files on disks.
○ Designed for searchable analog data.
➔NoSQL
○ Often schema-less databases.
○ MongoDB could be useful for searchable analog
data (Probably with GridFS Addon)
○ Watch this space...
Summary
Captured Analysed Moved RetrievedStored

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Managing Large Datasets in LabVIEW

  • 1. Managing Large Data Sets James McNally, CLA
  • 2. (Re-) Introduce Myself Twitter - @JamesMc86 www.wiresmithtech.com/blog www.jamesmcnally.co.uk (old)
  • 3.
  • 4. Why LabVIEW is Special Leading the way on dealing with live data: ● 1GB/s + Hardware Interface Support ● GPU Processing, Intel MKL Based Palettes ● Inherent Parallelism DATAFLOW
  • 5. Today ➔Life of Data ➔System Design ➔Techniques to Consider
  • 6. Data Must Be... Challenging at high speed or in large volumes. Captured Analysed Moved RetrievedStored
  • 7. The Battle Ground Real World CPU RAM HDD NAS or Network Services TB-PB128M-16GB GB-TB 50-500MB/s 0.1-1GB/s <10GB/s 1-120MB/s
  • 8. System Design Example AE Sensor x4 up to 500kHz DAQ Card 1MS/s AE Sensor x4 up to 500kHz DAQ Card 1MS/s x8 Total CPU 32MS/s Requirements - All events captured. - 30 second circular buffer to capture and show data from before the event. - Data for all channels must be stored, even if the event is on one channel.
  • 9. Some Considerations ➔Data Formats ○ e.g. DAQmx TDMS Files ➔Data Compression ➔Appropriate Rates ○ E.G. Reduction for Displays ➔64 Bit LabVIEW
  • 10. Algorithmic Complexity Understand how well your algorithms scale.
  • 11. DVRs
  • 12. DVR - Throw and Catch Guarantees no data copies in transit, whatever method is used.
  • 13. DVR - Nested Arrays ➔Reduces contiguous memory requirements. ➔Allows ‘odd’ shaped data allocations
  • 14. Databases - Wildly Generalised! ➔Great for ‘random’ retrieval ➔Good for providing data to other languages esp. web based ➔Design may be non-trivial ➔Bad for waveform data (traditionally) ➔Platform considerations for interfacing
  • 15. ‘Database’ Technology to Consider ➔Traditional Relational Databases ○ MySQL, PostgreSQL, SQL Server ○ Widely used and good online support ➔Datafinder ○ No database to see, indexes files on disks. ○ Designed for searchable analog data. ➔NoSQL ○ Often schema-less databases. ○ MongoDB could be useful for searchable analog data (Probably with GridFS Addon) ○ Watch this space...