pytimber.SparkLoggingDB
- class pytimber.SparkLoggingDB(appid: str = 'SPARKPYTIMBER4', clientid: str = 'PYTIMBER3', source: str = 'nxcals', loglevel: str | int | None = None, sparkconf: str | None = None, sparkprops: Mapping[str, str] | None = None, kerberosprincipal: str | None = None, kerberoskeytab: str | None = None, data_location: str = 'pro', spark_session: SparkSession | None = None, service_url: str = 'https://cs-ccr-nxcals6.cern.ch:19093,https://cs-ccr-nxcals7.cern.ch:19093,https://cs-ccr-nxcals8.cern.ch:19093', sparkloglevel: str | None = 'ERROR')
Methods
SparkLoggingDB.__init__([appid, clientid, ...])Initializes a new instance of the PyTimber client.
SparkLoggingDB.get(pattern_or_list, t1[, ...])Query for a list of variables or for variables whose name matches a pattern (string) in a time window from t1 to t2 and return corresponding variable(s) data.
SparkLoggingDB.getAligned(pattern_or_list, ...)Use get aligned instead
Use get_children_for_hierarchies instead
SparkLoggingDB.getDataUsingSnapshots(...[, ...])Use get_data_using_snapshots instead
SparkLoggingDB.getDescription(pattern)Use get_variable_description instead
SparkLoggingDB.getFundamentals(t1, t2, ...)Use get_fundamentals instead
Use get_hierarchies_for_variables instead
Use get_interval_by_lhc_modes instead
SparkLoggingDB.getLHCFillData([fill_number, ...])Use get_lhc_fill_data instead
SparkLoggingDB.getLHCFillsByTime(t1, t2[, ...])Use get_lhc_fills_by_time instead
SparkLoggingDB.getMetaData(pattern_or_list)Use get_meta_data instead
SparkLoggingDB.getScaled(pattern_or_list, t1, t2)Use get_scaled instead
SparkLoggingDB.getSnapshotNames(pattern_or_list)Use get_snapshot_names instead
SparkLoggingDB.getStats(pattern_or_list, t1, t2)Use get_variable_stats instead
SparkLoggingDB.getUnit(pattern)Use get_variable_unit instead
SparkLoggingDB.getVariable(variable, t1[, ...])Use get_variable instead
Use get_variables_for_hierarchies instead
Use get_variables_for_snapshots instead
Use get_variable_origin instead
SparkLoggingDB.get_aligned(pattern, t1, t2)Retrieves the aligned data for the given pattern of variables within the specified time range [t1, t2], based on the fundamental and master variable.
SparkLoggingDB.get_as_pivot(pattern_or_list, t1)Get a list of children hierarchy paths for given parent hierarchy paths.
Get data for variables attached to snapshots which are selected by provided list of strings or pattern in a time window defined in the snapshot configuration
SparkLoggingDB.get_fundamentals(t1, t2, pattern)Gets list of FundamentalVariable objects between two timestamps for a given pattern.
Get a list of hierarchy paths for variables (in which given variables are defined).
Returns a list of FillInterval objects for the given time window and two LHC beam modes
SparkLoggingDB.get_lhc_fill_data([fill_number])Gets times and beam modes for a particular LHC fill.
SparkLoggingDB.get_lhc_fills_by_time(...[, ...])Returns a list of LHC fills data that occurred within the specified time range.
SparkLoggingDB.get_meta_data(pattern)Retrieves metadata for vector variables (so called vector contexts) matching a pattern.
SparkLoggingDB.get_scaled(pattern, t1, t2[, ...])Retrieves the scaled data for the given pattern of variables in a time window from t1 to t2.
SparkLoggingDB.get_snapshot_names(...[, ...])Get a list of snapshots names based on a list of strings or a pattern, filtered by owner pattern and description pattern.
SparkLoggingDB.get_variable(variable, t1[, ...])Query for a specific variable within a time window and with the option to filter by fundamentals and return corresponding variable data.
Gets description(s) for the given variable pattern.
SparkLoggingDB.get_variable_origin(pattern)Gets the system origin(s) for the given variable pattern.
SparkLoggingDB.get_variable_stats(pattern, ...)Gets variable statistics for the specified time range.
SparkLoggingDB.get_variable_unit(pattern)Gets unit(s) for the given variable pattern.
Get a list of variables attached to hierarchies.
Get variables attached to snapshots.
SparkLoggingDB.search(pattern)Use search_variables instead
SparkLoggingDB.searchFundamental(fundamental, t1)Use search_fundamentals instead
SparkLoggingDB.search_fundamentals(...[, t2])Searches for fundamental variables names that match the specified pattern within the specified time range.
SparkLoggingDB.search_variables(pattern)Searches for variable names that match the given pattern.