toaster 0.5.2
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NEW FEATURES
* Graph function `computeGraphClusters` performs various types
of graph decomposition including connected components and
modularity (future release) (#33).
* Graph function `computeGraphClustersAsGraphs` uses community object
produced by `computeGraphClusters` to create graphs corresponding
to its components (#33).
* Function `validateGraph` validates and tests for consistency graph
tables in Aster (#34).
* Function `computeSample` now supports sample stratum based on
table column or custom stratum condition (#28).
* Function `getTableCounts` is handy when reviewing database tables
first time: it reports the number of rows and columns in each
table (#50).
* Function `computeCorrelations` now supports group columns in Aster
(with argument `by`) (#49).
MINOR FEATURES
* Graph vertices table is now always read when constructing
corresponding network object (#46).
* Minimal graph must have single vertex and no edges (#42).
* All plotting functions now support subtitle (#41).
* Deprecated function theme_empty - use ggplot2::theme_void
instead (#53).
BUG FIXES
* `getTableSummary` fails when table has one or more temporal column
types (#37)
* `getTablesummary` fails when numerical data contains 'NaN' or other
special values (#39, #51)
* `computeHeatmap` argument `by` now supports multiple columns
to group results (#44).
* Temporary table names allow underscore characters now (#40).
toaster 0.5.1
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NEW FEATURES
* New graph functionality expands toaster's reach to Aster graph
engine and SQL/GR functions (#32).
Simply define a metadata 'toagraph' object that describes a graph
data in Aster (one object per graph) to compute various graph
metrics and distributions:
- `computeGraphHistogram` returns degree, clustering,
shortest path, and various centrality measure distributions;
- `computeGraphMetric` returns top graph vertices for
given graph metric including degree, local clustering, and
various centrality measures.
New functions `computeGraph`, 'showGraph`, and `computeEgoGraph`
query Aster graph data to filter, inspect and visualize whole
or sub-graphs, including ego graphs (neighborhood graphs).
MINOR FEATURES
* `getTableSummary` can skip computing percentiles by setting
percentiles value to logical \code{FALSE} (#31).
* `getNullCounts()` new argument support percent and data frame
with no factors (#29).
* `isTable` now supports schema in table name, queries (by returning
NA), and expanded result format (#30).
toaster 0.4.2
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MINOR FEATURES
* `createMap` support for:
- locationName is a vector of the column names containing address,
name, etc. suitable to geocode (find latitude and longitude).
The columns are used in order of appearance: geocoding tries
1st column's values first, then, for the data points that didn't
get resolved, it tries the 2d column's values, and so on.
- shape's fill using 2d metric with argument `metrics`. This deprecates
parameter `metricName` (#25);
- transparency control argument `shapeAlpha` for the shapes on
the map (#24);
- new shape and stroke arguments `shape` and `shapeStroke` to manage
appearance of artifacts on the map.
* all plotting functions gain new guide parameter(s) that control
appearance of fill, size and other legend(s) using ggplot2
guide object name or object itself.
BUG FIXES
* Kmeans cluster and total within sum of squares calculations now
work when `scale=FALSE`. (fixes #23)
* Kmeans SQL is correct now when `id` is exactly one of the table columns
and default `aliasId`. (fixes #22)
* `showData` now uses same default theme_tufte as the rest of plotting
functions (missed it 0.4.1).
* fixed histograms in `showData` after upgrading to ggplot2 2.0.0
(missed it 0.4.1).
toaster 0.4.1
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NEW FEATURES
* K-means clustering function performs in-database data prep, scaling,
clustering, computing standard k-means measures and aggregated metrics
on produced clusters. Other functions include the silhouette method of
evaluating cluster consistency and validity and variety of
visualizations options. Result of k-means function is compatible with
stats 'kmeans' object.
* Utility getNullCounts function returns NULL counts per column
in the table.
MINOR FEATURES
* Upgraded plotting to ggplot2 2.0.0 and fixed test faiures attributed
to this upgrade.
* Changed default theme settings to theme_tufte from ggthemes package
for all plotting (create) functions.
* Updated some examples in the documentation.
* Added validation of RODBC connection (except checking for live
connection to a database).
toaster 0.3.1
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NEW FEATURES
* New text analysis functions `computeTf` and `computeTfIdf`
process corpora in Aster and produce results compatible with package tm,
in particular term document matrix.
* Both `computeTf` and `computeTfIdf` rank terms to return top ranked
ones. Ranking and number of terms to return are provided by
parameters `top` and `rankFunction`. Unlimited (all terms) are
returned by default with `top = NULL`.
* S3 classes `nGram` and `token` provide pluggable parsers to extract text
tokens to use in the functions 'computeTf' and 'computeTfIdf'.
* Text functions support stop words in both Aster (installed stopwords file)
and R (post-processing of results).
* Linear regression now is compatible with R standard lm functions returning
object of both classes c('toalm', 'lm'). This means methods `summary`,
`coefficients`, etc. work with the object returned by `computeLm`.
This change is not backward compatible: to obtain result returned in 0.2.5
list contains element `old.result`.
* To compute results similar to `lm` `computeLm` uses sample (default 1000
rows) to calculate stats like residuals, R-square, etc. in Aster. As before,
linear regression coefficients are calculated on full data set with
SQL/MR linreg function.
* `getTableSummary` is enabled for parallel execution. Simply create and
register parallel cluster of your choice with doParallel package and set
parameter parallel=TRUE. Performance gains may be up to 50% or better
depending on size of the table, number of parallel processes, and number
of columns. Run `demo("baseball-parallel")` for examples.
* `computePercentiles` is enabled for parallel execution. Simply create and
register parallel cluster of your choice with doParallel package and set
parameter parallel=TRUE. Performance gains may be up to 50% or better
depending on size of the table, number of parallel processes, and number
of columns. Run `demo("baseball-parallel")` for examples.
* Added support of temporal Aster data types in `getTableSummary` and
`computePercentiles`. Temporal types are date, time, timestamp, and interval.
in `computePercentiles` set parameter temporal=TRUE to calculate
temporal columns and run it separately from numerical ones.
MINOR FEATURES
* Added factory functions `getDiscretePaletteFactory` and `getGradientPaletteFactory`
to dynamically generate palettes with n number of colors.
* Added utility function `isTable` that checks if tables exist in Aster database.
* Parameter `formula` replaced defunct `expr` in the function `computeLm`
for consistency with other model-fitting functions.
* `computePercentiles` now operates on multiple columns at once.
* Improved database error handling to be more robust and informative. Error messages
now include both ODBC and Aster error message and information (when applicable).
* Added deprecated warning facility `toa_dep` similar to ggplot2 gg_dep
function.
BUG FIXES
* Legend position in `showData` histogram format is completely removed if
legendPosition="none".
* `computePercentiles` now returns no rows for the column that contains all NULLs.
Before it threw error without completing.
* fixed legend position in plotting functions.
* Added error when histogram start value is greater than end value in (Issue #33)
DOCUMENTAION
* Completely reworked demo scripts. Now they contain fully functional examples
running on baseball and openDallas data sets. The data sets are available
from github: https://bitbucket.org/grigory/toaster/downloads
- baseball demo: https://raw.githubusercontent.com/wiki/teradata-aster-field/toaster/downloads/baseball.zip
- Dallas demo: https://raw.githubusercontent.com/wiki/teradata-aster-field/toaster/downloads/dallasopendata.zip
* Baseball Lahman data set now includes 2013 season.
toaster 0.2.5
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NEW FEATURES
* `computeSample`: randomly sample data from the table specifying
fraction or size of desired data set.
* `createMap`: new visualization function for combining maps with data
artifacts from Aster database. Can be used to produce maps of
arbitrary scale (with exception of whole world) and type with shapes
of size and labels corresponding to data computed in Aster. It uses
ggmap and ggplot2 packages and Google API for geocoding data as
necessary. It implements smart logic to choose map tiles to place
geocoded data appropriately, and it also automatically geocodes
data if necessary (Google API restrictions apply).
* Due to geocoding and map API restrictions `createMap` supports
function caching suggesting function `memoise` of memoise package.
(other functions are fine too). Properly following suggested practices
should significantly optimize both peformance and API usage when geocoding
or retrieving maps.
* `compute`: for executing arbitrary aggregations on Aster tables.
* `computeBarchart`: for computing data for barchart visualizations. This
is different from `computeHistogram` as barchart is defined on factors
(categorical data) witch doesn't support defining bins like in histograms.
* `computePercentiles`: for computing multiple percentiles across one or
many subsets of a table in one go. Results are suitable for function
`createBoxplot` (see next).
* `createBoxplot`: visualizes boxplots for single column across one or
multiple subsets.
* `computeLm`: compute linear model coefficients similar to lm function but
all performed inside Aster.
ENHANCEMENTS
* added parameter `test` to compute- functions (functions that access and
manipulate data in Aster) to produce SQL without executing it. Thus, when
`test=TRUE` function returns string containing SQL that would have run
in Aster.
* package depedencies moved from Depends to Imports section of DESCRIPTION file
except for RODBC package. Keeping RODBC in Depends because toaster requires
access to RODBC connection object and to its function `odbcConnect`. Other
packages are not exposed by toaster functions so accessing them would have
been needed only for advanced usage (if any).
if you use any function from the packages other than RODBC then those packages
should be loaded with `library` or `require` or use their namespace.
* facet parameter now supports both one-value and 2-value vector (if parameter
is longer than the rest of values are ignored). Single value defines column
name for wrapping facets in 1 or more column lattice. Two values define pair
of columns to place facets in 2-dimensional grid for each combination of
values found.
* `createHistogram` supports trend lines with parameter trendLine=TRUE.
* `computeHeatmap` converts dimension and facet columns to factors by default.
If undesired set parameter dimAsFactor = FALSE to disable (not recommended
with heat maps).
* `computeHeatmap` now supports withMelt to melt result using function melt
from package reshape2. This option simplifies visualizating with facets.
* `createBubblechart` now supports scaling shapes by size (default) or by area.
Correspondingly, use shapeSizeRange when scaling by size; and shapeMaxSize
when scaling by area.
* `createBubblechart` added parameters to control label positioning and
formatting. All parameters that position and format label text start
with prefix "label" now. Old parameters textSize, textColour, and
textVJust renamed to labelSize, labelColour, labelVJust.
* `createPopPyramid` support for facets.
* added utility method to list Aster data types: `getNumericTypes`,
`getCharacterTypes`, `getTemporalTypes`.
* `computeAggregates` is not an alias anymore and it replaced function
`compute` which is no more.