Changelog¶
The format is based on Keep a Changelog and this project adheres to Semantic Versioning.
0.4.2 (2020-07-16)¶
Added¶
Kafka streaming data source through
store.Store.load_kafka()
.session.Session.endpoint()
decorator adds HTTP endpoints to the session from a Python callback.array.sort()
has a newascending
parameter.True
by default, it allows to choose the sorting order.scope.cumulative()
has a newdense
parameter.False
by default, it allows to choose whether to include all of a level’s members in the cumulative aggregation, even those for which the underlying measure has no values.Atoti+ now supports i18n.
en-US
is the only locale supported by default but additional locales can be made available by providing custom translation files. These can be configured withconfig.create_config()
A good starting point for adding new locales is to use the template containing all the translatable items, which can be obtained by usingsession.Session.export_translations_template()
.The Gauss error function
math.erf()
and its complementarymath.erfc()
(#92).
Changed¶
The
name_attribute
parameter used to select the displayed username when using an OpenID Connect can be configured.The
scope
parameter used to select the requested scopes when using an OpenID Connect provider can be configured. Theopenid
scope is always passed by default.
Fixed¶
Missing images in the tutorial (#80).
Issue when reading pandas DataFrame with
NaN
(#77).hierarchy.Hierarchy.isin()
andlevel.Level.isin()
can be used with more than 2 values (#93).Issue with array types not displayed correctly in the stores schema.
Issue when joining a column of type int to a column of type long if the store is based on a parquet file (#76).
0.4.1.0 (2020-06-17)¶
Added¶
New tutorial exploring the main basic features of atoti.
rank()
returns a measure ranking the members of a given hierarchy based on the value of another measure.array.prefix_sum()
performs the prefix sum of array measures.Hierarchies can have the same name if they are in different dimensions. To avoid conflicts, a hierarchy can be accessed via a tuple containing the dimension and the hierarchy:
cube.hierarchies["Product", "Size"]
.
Changed¶
Bumped the minimal required version of JupyterLab to 2.1.
Upgraded from ActiveUI SDK 4.3.7 to 4.3.8.
Better messages for Java known errors (#43).
The Auth0 support in Atoti+ has been replaced by the more general OpenID Connect authentication protocol. The structure of the configuration can be seen in the configuration tutorial.
Fixed¶
filter()
’smeasure
parameter accepts any value that can be converted to a measure (#22).filter()
andwhere()
support inequalities on dates as conditions.Issue when loading data into a scenario with
truncate
set toTrue
(#53).Issue with
agg.quantile()
combined withscope.origin()
.Issue when aggregating
.VALUE
measures using any of theagg.xxx
functions (#52).Type issue that sometimes happened when chaining operators such as
array.quantile()
anddate_shift()
.Blinking cell updates not appearing in pivot tables with real time queries.
0.4.0 (2020-05-25)¶
Added¶
agg.max_member()
andagg.min_member()
return a measure equal to the member reaching the correspinding extremum of the passed measure on the given level.hierarchy.Hierarchy.isin()
,query.hierarchy.QueryHierarchy.isin()
,level.Level.isin()
, andquery.level.QueryLevel.isin()
create conditions expressing that a hierarchy or a level should be on one of the given members.stores.Stores.schema
andcube.Cube.schema
: SVG graphs of, respectively, all the session’s stores and the stores used by a cube.store.StoreScenarios.load_csv()
loads a directory of CSV files into a store, automatically generating scenarios based on the directory’s structure.total()
returns the total value on each hierarchy member.session.Session.create_store()
creates an empty store from a schema.Exponentiation operation between measures:
measure_a ** measure_b
.
Changed¶
BREAKING: Hierarchies, levels, and measures can no longer be passed by name, instances of the corresponding class are expected instead.
BREAKING:
atoti.create_session()
’sport
,max_memory
,java_args
andsampling_mode
parameters and theATOTI_URL_PATTERN
environment variable have been moved to theconfig.SessionConfiguration
changing these signatures:create_session()
:(name='Unnamed', sampling_mode=SamplingMode(name='limit_lines', parameters=[10000]), port=None, max_memory=None, java_args=None, config=None, **kwargs)
→(name='Unnamed', *, config=None)
config.create_config()
:(inherit=True, metadata_db=None, roles=None, authentication=None, properties=None)
→(*, inherit=True, port=None, url_pattern=None, metadata_db=None, roles=None, authentication=None, sampling_mode=None, max_memory=None, java_args=None)
BREAKING: New structure for the authentication configuration in YAML as shown in the
configuration tutorial <tutorial/02-configuration:Auth0>
.BREAKING:
config.BasicUser.roles
andconfig.Auth0Authentication.role_mapping
do not accept role instances anymore, only role names.BREAKING: The wildcard value in measure simulations has been changed from
*
toNone
.BREAKING:
session.Session.read_pandas()
,session.Session.read_spark()
andsession.Session.read_numpy()
require a name for the created store:session.Session.read_numpy()
:(data, columns, store_name, keys, in_all_scenarios=True, partitioning=None, sep='|')
→(array, columns, store_name, *, keys=None, in_all_scenarios=True, partitioning=None, **kwargs)
session.Session.read_pandas()
:(dataframe, keys=None, store_name=None, partitioning=None, types=None, **kwargs)
→(dataframe, store_name, *, keys=None, in_all_scenarios=True, partitioning=None, types=None, **kwargs)
session.Session.read_spark()
:(dataframe, keys=None, store_name=None, partitioning=None)
→(dataframe, store_name, *, keys=None, in_all_scenarios=True, partitioning=None)
BREAKING:
simulation.Scenario.insert(row)
andstore.Store.insert_rows(rows)
have been renamedsimulation.Scenario.append()
andstore.Store.append()
. They take a variadic*rows
parameter and in place addition of a single row is still supported with+=
.BREAKING:
percentile
andvariance
functions have been renamedquantile
andvar
:agg.percentile(measure, percentile_value, mode='inc', interpolation='linear', scope=None)
→agg.quantile()
and(measure, q, *, mode='inc', interpolation='linear', scope=None)
array.percentile(measure, percentile_value, mode='inc', interpolation='linear')
→array.quantile()
and(measure, q, *, mode='inc', interpolation='linear')
agg.variance(measure, mode='sample', scope=None)
→agg.var()
and(measure, *, mode='sample', scope=None)
array.variance(measure, mode='sample')
→array.var()
and(measure, *, mode='sample')
BREAKING:
avg
has been renamedmean
with .MEAN suffix for automatically created measures instead of .AVG:agg.avg(measure, scope=None)
→agg.mean()
and(measure, *, scope=None)
array.avg()
→array.mean()
BREAKING: Some function signatures have changed:
cube.Cube.create_parameter_hierarchy()
:(level_and_hierarchy_name, members, indices=None, slicing=True, index_measure='', level_type=None)
→(name, members, *, data_type=None, index_measure=None, indices=None, store_name=None)
whereslicing
has been removed since it can be set afterwards through:hierarchy.Hierarchy.slicing
.parent_value()
:(measure, on_hierarchies=None, top_value=None)
→(measure, on, *, apply_filters=False, degree=1, total_value=None)
. The two new parameters default to values equivalent to the previous behavior; see the function documentation for more details.scope.cumulative()
:(level, partitioning=None, window=range(-2147483648, 0), exclude_self=False)
→(level, *, partitioning=None, window=range(-2147483648, 0), exclude_self=False)
wherewindow
can also accept a tuple of two time offsets to perform a rolling time period aggregation.simulation.Scenario.load_csv()
:(file, delimiter=',')
→(path, *, sep=',')
BREAKING: Some other function signatures have changed only to adopt keyword-only parameters (denoted by a
*
in the parameter list):Upgraded from ActiveUI SDK 4.3.5 to 4.3.7. Pivot tables support new Tree, Pivot, and Table layouts, the latter making the Tabular View widget redundant so it has been removed from the available widgets.
session.Session.read_pandas()
,store.Store.load_pandas()
,simulation.Simulation.load_pandas()
, andsimulation.Scenario.load_pandas()
automatically load columns made of numerical Python lists or Numpy one-dimensional ndarrays as arrays.Stores without key columns are partitioned on their non-numerical columns by default.
Changed the behavior of
agg.single_value()
aggregation function to be more consistent with other aggregation functions (#40).Cube names are not restricted to alphanumeric strings without spaces anymore.
The
path
parameter of all CSV loading functions accepts glob patterns (e.g./path/**/*.csv
).
Removed¶
BREAKING:
simulation.Priority
. Directly pass numbers to rank simulation rules instead.BREAKING:
Cube.create_bucketing()
has moved toCube._setup_bucketing()
and is not part of the public API anymore. It might change in future releases without notice.BREAKING:
config.create_config()
’sproperties
parameter.max_memory
can be passed directly as a named-parameter instead. The other properties have been removed.BREAKING:
pow(measure_a, measure_b)
replaced bymeasure_a ** measure_b
.
Fixed¶
Inability to install atoti alongside Python > 3.7 when using Conda.
Issue with
filter()
not being aggregated correctly (#17, #28).Metadata DBs created in atoti can be used in Atoti+ and reciprocally (#15).
Inability to create some measures or hierarchies after some partial joins (#4, #10).
Inability to load CSV folders from AWS S3 storage.
Slow read of files on AWS S3 when anonymous due to multiple timeouts in the credentials provider (#26).
Inability to use wildcards on fields types other than strings.
Inability to use numeric levels for measure simulations.
0.3.1 (2020-04-14)¶
First public release of atoti.