History Server

1
History Server API

• Christopher Larrieu
• Jefferson Laboratory

2
Goals

• Simple interface to archived data
• Efficient access to distributed data sources
• Useful data manipulation capabilities
• Portable integration with existing EPICS tools

3
CADataStore abstract interface to read CA data
from file, db, etc.

• archive
• Provides channel listing, creates data range
  objects
• range
• Describes data for one channel on time range
• channel_state
• Complete information for one channel associated
  with one point in time.
• range_iterator
• Access sequential channel states by updating
  channel_state

4
Server Specialization

• Server accesses CA archive via CADataStore object
• Different derived classes for different archives
• LANL_DataStore wraps around Kays archive API
• JLAB_DataStore wraps around JLAB archive API
• RDB_DataStore ?
• _DataStore
• Derived classes compiled as shared object code,
  loaded at run-time.
• Narrow interface eases specialization, but
  captures essential functionality.

5
Server Schematic
History Data Client
History Server
LANL_DataStore
Channel Archiver API
6
Server Components

• Data access plug-in (derived from CADataStore)
• Exported network interface
• Archive description (name, acquisition mode,
  etc.)
• Data manipulation (transform library)
• Data production (data stream, iterator)
• Network communication component

7
Client Components

• Consumer code (e.g. data mining, visualization)
• Library API
• Directory Services
• Data manipulation (transform library)
• Data consumption (stream from server)
• Network communication component

8
DataStoreDirectory

• Provides hierarchical structure to signal names
• Enumerates registered history servers
• Name
• Location
• Data quality
• Maps signal names to history servers

9
DataSequence

• Describes a stream of sequenced data
• Every element contains
• Indexing attribute (scalar, numeric) (e.g. time)
• Primary attribute (e.g. value)
• Ancillary attributes (e.g. status, severity,
  units)
• Attribute dependencies (e.g. alarm depends upon
  value)
• Elements are iterated over via the indexing
  attribute, and return primary attribute as
  default value.

10
DataTransform

• Reads input sequence, generates output sequence.
• Generic transforms operate upon primary
  attribute.
• Specialized transforms operate on known
  attributes.

11
Example 1 Binning Transform

• Parameters bin width
• Input (index,value) pairs (e.g. time, value)
• All other attributes discarded
• Output (count, mean, variance, min, max) tuples,
  indexed by bin number, with mean as primary
  attribute.

12
Example 2 Discrete Fourier Transform

• Input (index, value) pairs (e.g. time, value)
• All other attributes discarded
• Output (frequency, amplitude) pairs, index by
  frequency, with amplitude as primary attribute.

13
Standard Transforms

• Binning
• Interpolating
• Decimating
• DFT, IDFT
• Digital Filter
• Averaging
• Rasterizing
• Attribute Mapping
• Attribute Filtering

14
Network Communication

• CORBA
• Transparent binary compatibility
• Easy communication between distributed objects
• Integrate with other CORBA-enabled tools
• MICO
• open source implementation
• branded CORBA 2.3 compliant by OMG
• Portable Unix (hp-ux, linux, solaris, aix,
  etc.), Win32
• C, Java bindings

15
Uses in EPICS

• Portable CA Server interface can supply history
  data to ca clients (e.g. medm) .
• Adaptor library supporting Kays API current
  applications become network capable.
• New applications java tools, etc.

16
Intended Use at JLAB

• StripTool history plug-in
• Replacement for current XARR interface
• Operator / user scripting.
• DARTH (vaporous data-mining tool)