Table Of Contents

REST API Commands


Command List

Command Name (explained here) Description
frame/add_columns Add columns to current frame.
frame/assign_sample Randomly group rows into user-defined classes.
frame/bin_column Classify data into user-defined groups.
frame/bin_column_equal_depth Classify column into groups with the same frequency.
frame/bin_column_equal_width Classify column into same-width groups.
frame/categorical_summary Build summary of the data.
frame/classification_metrics Model statistics of accuracy, precision, and others.
frame/column_median Calculate the (weighted) median of a column.
frame/column_mode Evaluate the weights assigned to rows.
frame/column_summary_statistics Calculate multiple statistics for a column.
frame/copy New frame with copied columns.
frame/correlation Calculate correlation for two columns of current frame.
frame/correlation_matrix Calculate correlation matrix for two or more columns.
frame/count_where Counts qualified rows.
frame/covariance Calculate covariance for exactly two columns.
frame/covariance_matrix Calculate covariance matrix for two or more columns.
frame/cumulative_percent [BETA] Add column to frame with cumulative percent sum.
frame/cumulative_sum [BETA] Add column to frame with cumulative percent sum.
frame/daal_pca [ALPHA] <Missing Doc>
frame/dot_product [ALPHA] Calculate dot product for each row in current frame.
frame/drop_columns Remove columns from the frame.
frame/drop_duplicates Modify the current frame, removing duplicate rows.
frame/ecdf Builds new frame with columns for data and distribution.
frame/entropy Calculate the Shannon entropy of a column.
frame/export_to_csv Write current frame to HDFS in csv format.
frame/export_to_hbase Write current frame to HBase table.
frame/export_to_hive Write current frame to Hive table.
frame/export_to_jdbc Write current frame to JDBC table.
frame/export_to_json Write current frame to HDFS in JSON format.
frame/flatten_columns Spread data to multiple rows based on cell data.
frame/group_by [BETA] Summarized Frame with Aggregations.
frame/histogram [BETA] Compute the histogram for a column in a frame.
frame/quantiles New frame with Quantiles and their values.
frame/rename Change the name of the current frame.
frame/sort [BETA] Sort by one or more columns.
frame/sorted_k [ALPHA] Get a sorted subset of the data.
frame/tally [BETA] Count number of times a value is seen.
frame/tally_percent [BETA] Compute a cumulative percent count.
frame/top_k Most or least frequent column values.
frame/unflatten_columns Compacts data from multiple rows based on cell data.
frame:/filter Select all rows which satisfy a predicate.
frame:/helloworld This is a Hello World Plugin for Frame.
frame:/join [BETA] Join two data frames (similar to SQL JOIN).
frame:/load Append data from a CSV/XML into an existing (possibly empty) frame
frame:/mapreducewordcount Counts and reports the top 10 words across all columns with string data in a frame.
frame:/rename_columns Rename columns
frame:/wordcount Counts and reports the top 10 words across all columns with string data in a frame.
frame:edge/add_edges Add edges to a graph.
frame:edge/rename_columns Rename columns for edge frame.
frame:vertex/add_vertices Add vertices to a graph.
frame:vertex/drop_duplicates Remove duplicate vertex rows.
frame:vertex/filter  
frame:vertex/rename_columns Rename columns for vertex frame.
graph/annotate_degrees Make new graph with degrees.
graph/annotate_weighted_degrees Calculates the weighted degree of each vertex with respect to an (optional) set of labels.
graph/clustering_coefficient Coefficient of graph with respect to labels.
graph/copy Make a copy of the current graph.
graph/graphx_connected_components Implements the connected components computation on a graph by invoking graphx api.
graph/graphx_label_propagation [ALPHA] Implements the label propagation computation on a graph by invoking graphx api.
graph/graphx_pagerank Determine which vertices are the most important.
graph/graphx_triangle_count Number of triangles among vertices of current graph.
graph/rename Rename a graph in the database.
graph/vertex_outdegree Counts the out-degree of vertices in a graph.
graph:/define_edge_type Define an edge type.
graph:/define_vertex_type Define a vertex type by label.
graph:/edge_count Get the total number of edges in the graph.
graph:/kclique_percolation [ALPHA] Find groups of vertices with similar attributes.
graph:/label_propagation Classification on sparse data using Belief Propagation.
graph:/loopy_belief_propagation Classification on sparse data using Belief Propagation.
graph:/vertex_count Get the total number of vertices in the graph.
model/rename Rename a model.
model:collaborative_filtering/new Create a new Collaborative Filtering (ALS) model.
model:collaborative_filtering/predict [BETA] Collaborative Filtering Predict (ALS).
model:collaborative_filtering/recommend [BETA] Collaborative Filtering Predict (ALS).
model:collaborative_filtering/score [BETA] Collaborative Filtering Predict (ALS).
model:collaborative_filtering/train Collaborative filtering (ALS) model
model:daal_linear_regression/new [ALPHA] Create a ‘new’ instance of a Linear Regression model.
model:daal_linear_regression/predict [ALPHA] Make new frame with column for label prediction.
model:daal_linear_regression/train [ALPHA] Build linear regression model.
model:k_means/new Create a ‘new’ instance of a k-means model.
model:k_means/predict [BETA] Predict the cluster assignments for the data points.
model:k_means/publish [BETA] Creates a tar file that will be used as input to the scoring engine
model:k_means/train [BETA] Creates KMeans Model from train frame.
model:lda/new Creates Latent Dirichlet Allocation model
model:lda/predict [ALPHA] Predict conditional probabilities of topics given document.
model:lda/publish [ALPHA] Creates a tar file that will used as input to the scoring engine
model:lda/train [ALPHA] Creates Latent Dirichlet Allocation model
model:libsvm/new [ALPHA] Create a ‘new’ instance of a Support Vector Machine model.
model:libsvm/predict [ALPHA] New frame with new predicted label column.
model:libsvm/publish [BETA] Creates a tar file that will be used as input to the scoring engine
model:libsvm/score [ALPHA] Calculate the prediction label for a single observation.
model:libsvm/test [ALPHA] Predict test frame labels and return metrics.
model:libsvm/train [ALPHA] Train a Lib Svm model
model:linear_regression/new Create a ‘new’ instance of a Linear Regression model.
model:linear_regression/predict [ALPHA] Make new frame with column for label prediction.
model:linear_regression/train [ALPHA] Build linear regression model.
model:logistic_regression/new Create a ‘new’ instance of logistic regression model.
model:logistic_regression/predict [ALPHA] Predict labels for data points using trained logistic regression model.
model:logistic_regression/test [ALPHA] Predict test frame labels and return metrics.
model:logistic_regression/train [ALPHA] Build logistic regression model.
model:naive_bayes/new Create a ‘new’ instance of a Naive Bayes model
model:naive_bayes/predict [ALPHA] Predict labels for data points using trained Naive Bayes model.
model:naive_bayes/publish [ALPHA] Creates a scoring engine tar file.
model:naive_bayes/test [ALPHA] Predict test frame labels and return metrics.
model:naive_bayes/train [ALPHA] Build a naive bayes model.
model:power_iteration_clustering/new Create a ‘new’ instance of a PowerIterationClustering model.
model:power_iteration_clustering/predict Predict the clusters to which the nodes belong to
model:principal_components/new Create a ‘new’ instance of a Principal Components model.
model:principal_components/predict [ALPHA] Predict using principal components model.
model:principal_components/publish [BETA] Creates a tar file that will be used as input to the scoring engine
model:principal_components/train Build principal components model.
model:random_forest_classifier/new Create a ‘new’ instance of a Random Forest Classifier model.
model:random_forest_classifier/predict [ALPHA] Predict the labels for the data points.
model:random_forest_classifier/publish [BETA] Creates a tar file that will be used as input to the scoring engine
model:random_forest_classifier/test [ALPHA] Predict test frame labels and return metrics.
model:random_forest_classifier/train [ALPHA] Build Random Forests Classifier model.
model:random_forest_regressor/new Create a ‘new’ instance of a Random Forest Regressor model.
model:random_forest_regressor/predict [ALPHA] Predict the values for the data points.
model:random_forest_regressor/publish [BETA] Creates a tar file that will be used as input to the scoring engine
model:random_forest_regressor/train [ALPHA] Build Random Forests Regressor model.
model:svm/new [ALPHA] Create a ‘new’ instance of a Support Vector Machine model.
model:svm/predict [ALPHA] Predict the labels for the data points
model:svm/publish [BETA] Creates a tar file that will be used as input to the scoring engine
model:svm/test [ALPHA] Predict test frame labels and return metrics.
model:svm/train [ALPHA] Build SVM with SGD model