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HCL OneDB V1.0.0.0
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HCL OneDB™
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Extending
Beyond standard relational database objects,
HCL OneDB™
can be extended to handle specialized data types, access methods, routines, and other objects.
HCL OneDB™
includes many built-in extensions that are fully integrated in the database server.
HCL OneDB™
also provides modules, which are packages of extended database objects for a particular purpose and that are installed separately from the database server. Alternatively, you can create your own user-defined objects for
HCL OneDB™
.
extensions and modules
These topics describe how to use built-in database extensions and separately installed modules.
TimeSeries Data User's Guide
The
HCL OneDB™ TimeSeries Data User's Guide
contains information to assist you in using the TimeSeries extension with
HCL OneDB™
.
Time series API routines
The time series application programming interface routines allow application programmers to directly access a time series datum.
Data structures for the time series API
The time series API uses four data structures.
Extending
Beyond standard relational database objects,
HCL OneDB™
can be extended to handle specialized data types, access methods, routines, and other objects.
HCL OneDB™
includes many built-in extensions that are fully integrated in the database server.
HCL OneDB™
also provides modules, which are packages of extended database objects for a particular purpose and that are installed separately from the database server. Alternatively, you can create your own user-defined objects for
HCL OneDB™
.
extensions and modules
These topics describe how to use built-in database extensions and separately installed modules.
Database Extensions User's Guide
The
HCL OneDB™
Database Extensions User's Guide
explains how to use the database extensions that come with
HCL OneDB™
: Large Object Locator, MQ messaging, binary data types, basic text search, node data type,
HCL OneDB™
web feature service for Geospatial Data,
and SQL packages.
Performing XML Publishing
The
HCL OneDB™
XML User's Guide
includes information about using built-in functions for XML publishing with
HCL® OneDB®
.
Excalibur Text Search Module User's Guide
These topics describe the module and how to access and use its components.
Spatial Data User's Guide
The
HCL OneDB™ Spatial Data User's Guide
contains information to assist you in using the
HCL® OneDB®
spatial extension. The
HCL® OneDB®
spatial extension adds custom data types and supporting routines to the server.
Spatiotemporal Search for Moving Objects User's Guide
The
HCL OneDB™ Spatiotemporal Search for Moving Objects User's Guide
describes how to program applications to search data from moving objects in
HCL OneDB™
databases using the spatiotemporal search extension.
TimeSeries Data User's Guide
The
HCL OneDB™ TimeSeries Data User's Guide
contains information to assist you in using the TimeSeries extension with
HCL OneDB™
.
TimeSeries solution
Database administrators and applications developers use the TimeSeries solution to store and analyze time series data.
Data types and system tables
Specialized data types and system tables handle time series data.
Create and manage a time series through SQL
Before you can load time series data into the database, you must configure database objects specific to your time series. You can manage data storage and remove data as necessary. You can run SQL statements to create and manage time series.
Virtual tables for time series data
A virtual table provides a relational view of your time series data.
Pattern matching searches
You can search time series data for matches to a particular pattern of values. For example, after you identify a pattern of abnormal electricity usage that indicates an outage, you can search for matches to that pattern to find other outages. Pattern matching searches find matches to a pattern that you supply. Pattern matching searches do not discover patterns in time series data.
Advanced analytics
Advanced analytics functions provide specialized methods of analyzing time series data for patterns or abnormalities.
Calendar pattern routines
You can use calendar pattern routines to manipulate calendar patterns.
Calendar routines
You can use calendar routines to manipulate calendars.
Time series SQL routines
Time series API routines
The time series application programming interface routines allow application programmers to directly access a time series datum.
Differences in using functions on the server and on the client
There are significant differences between using the client version of the time series API (
tsfeapi
) and the server version of the time series API (
tsbeapi
).
Data structures for the time series API
The time series API uses four data structures.
The ts_timeseries structure
The ts_tscan structure
The ts_tsdesc structure
The ts_tselem structure
Time series API routines sorted by task
Time series API routines are sorted into logical areas based on the type of task.
The ts_begin_scan() function
The ts_cal_index() function
The ts_cal_pattstartdate() function
The ts_cal_range() function
The ts_cal_range_index() function
The ts_cal_stamp() function
The ts_cal_startdate() function
The ts_close() function
The ts_closest_elem() function
The ts_col_cnt() function
The ts_col_id() function
The ts_colinfo_name() function
The ts_colinfo_number() function
The ts_copy() function
The ts_create() function
The
ts_create()
function creates a time series.
The ts_create_with_metadata() function
The
ts_create_with_metadata()
function creates a time series with user-defined metadata attached.
The ts_current_offset() function
The ts_current_timestamp() function
The ts_datetime_cmp() function
The ts_del_elem() function
The ts_elem() function
The TS_ELEM_HIDDEN macro
The TS_ELEM_NULL macro
The ts_elem_to_row() function
The ts_end_scan() procedure
The ts_first_elem() function
The ts_free() procedure
The ts_free_elem() procedure
The ts_get_all_cols() procedure
The ts_get_calname() function
The ts_get_col_by_name() function
The ts_get_col_by_number() function
The ts_get_compressed() function
The
ts_get_compressed()
function returns the compression string if the time series data is compressed.
The ts_get_containername() function
The ts_get_flags() function
The ts_get_hertz() function
The
ts_get_hertz()
function returns the frequency for packed hertz data.
The ts_get_metadata() function
The ts_get_origin() function
The ts_get_packed() function
The
ts_get_packed()
function returns whether the specified time series contains packed data.
The ts_get_stamp_fields() procedure
The ts_get_threshold() function
The ts_get_ts() function
The ts_get_typeid() function
The ts_hide_elem() function
The ts_index() function
The ts_ins_elem() function
The TS_IS_INCONTAINER macro
The TS_IS_IRREGULAR macro
The ts_last_elem() function
The ts_last_valid() function
The ts_make_elem() function
The ts_make_elem_with_buf() function
The ts_make_stamp() function
The ts_nelems() function
The ts_next() function
The ts_next_valid() function
The ts_nth_elem() function
The ts_open() function
The
ts_open()
function opens a time series.
The ts_previous_valid() function
The ts_put_elem() function
The ts_put_elem_no_dups() function
The ts_put_last_elem() function
The ts_put_nth_elem() function
The ts_put_ts() function
The ts_reveal_elem() function
The ts_row_to_elem() function
The ts_time() function
The ts_tstamp_difference() function
The ts_tstamp_minus() function
The ts_tstamp_plus() function
The ts_update_metadata() function
The ts_upd_elem() function
Appendixes
Creating extensions
You can create user-defined data types, routines, access methods, and other database objects to suit your needs. You can use application programming interfaces to write user-defined routines and applications that access data in databases.
Data structures for the time series API
The time series API uses four data structures.
The ts_timeseries structure
The ts_tscan structure
The ts_tsdesc structure
The ts_tselem structure