Man pages for sparklyr
R Interface to Apache Spark
| arrow_enabled_object | Determine whether arrow is able to serialize the given R... |
| checkpoint_directory | Set/Get Spark checkpoint directory |
| collect | Collect |
| collect_from_rds | Collect Spark data serialized in RDS format into R |
| compile_package_jars | Compile Scala sources into a Java Archive (jar) |
| connection_config | Read configuration values for a connection |
| connection_is_open | Check whether the connection is open |
| connection_spark_shinyapp | A Shiny app that can be used to construct a 'spark_connect'... |
| copy_to | Copy To |
| copy_to.spark_connection | Copy an R Data Frame to Spark |
| DBISparkResult-class | DBI Spark Result. |
| distinct | Distinct |
| download_scalac | Downloads default Scala Compilers |
| dplyr_hof | dplyr wrappers for Apache Spark higher order functions |
| ensure | Enforce Specific Structure for R Objects |
| fill | Fill |
| filter | Filter |
| find_scalac | Discover the Scala Compiler |
| ft_binarizer | Feature Transformation - Binarizer (Transformer) |
| ft_bucketizer | Feature Transformation - Bucketizer (Transformer) |
| ft_chisq_selector | Feature Transformation - ChiSqSelector (Estimator) |
| ft_count_vectorizer | Feature Transformation - CountVectorizer (Estimator) |
| ft_dct | Feature Transformation - Discrete Cosine Transform (DCT)... |
| ft_elementwise_product | Feature Transformation - ElementwiseProduct (Transformer) |
| ft_feature_hasher | Feature Transformation - FeatureHasher (Transformer) |
| ft_hashing_tf | Feature Transformation - HashingTF (Transformer) |
| ft_idf | Feature Transformation - IDF (Estimator) |
| ft_imputer | Feature Transformation - Imputer (Estimator) |
| ft_index_to_string | Feature Transformation - IndexToString (Transformer) |
| ft_interaction | Feature Transformation - Interaction (Transformer) |
| ft_lsh | Feature Transformation - LSH (Estimator) |
| ft_lsh_utils | Utility functions for LSH models |
| ft_max_abs_scaler | Feature Transformation - MaxAbsScaler (Estimator) |
| ft_min_max_scaler | Feature Transformation - MinMaxScaler (Estimator) |
| ft_ngram | Feature Transformation - NGram (Transformer) |
| ft_normalizer | Feature Transformation - Normalizer (Transformer) |
| ft_one_hot_encoder | Feature Transformation - OneHotEncoder (Transformer) |
| ft_one_hot_encoder_estimator | Feature Transformation - OneHotEncoderEstimator (Estimator) |
| ft_pca | Feature Transformation - PCA (Estimator) |
| ft_polynomial_expansion | Feature Transformation - PolynomialExpansion (Transformer) |
| ft_quantile_discretizer | Feature Transformation - QuantileDiscretizer (Estimator) |
| ft_regex_tokenizer | Feature Transformation - RegexTokenizer (Transformer) |
| ft_r_formula | Feature Transformation - RFormula (Estimator) |
| ft_robust_scaler | Feature Transformation - RobustScaler (Estimator) |
| ft_standard_scaler | Feature Transformation - StandardScaler (Estimator) |
| ft_stop_words_remover | Feature Transformation - StopWordsRemover (Transformer) |
| ft_string_indexer | Feature Transformation - StringIndexer (Estimator) |
| ft_tokenizer | Feature Transformation - Tokenizer (Transformer) |
| ft_vector_assembler | Feature Transformation - VectorAssembler (Transformer) |
| ft_vector_indexer | Feature Transformation - VectorIndexer (Estimator) |
| ft_vector_slicer | Feature Transformation - VectorSlicer (Transformer) |
| ft_word2vec | Feature Transformation - Word2Vec (Estimator) |
| full_join | Full join |
| generic_call_interface | Generic Call Interface |
| get_spark_sql_catalog_implementation | Retrieve the Spark connection's SQL catalog implementation... |
| grapes-greater-than-grapes | Infix operator for composing a lambda expression |
| hive_context_config | Runtime configuration interface for Hive |
| hof_aggregate | Apply Aggregate Function to Array Column |
| hof_array_sort | Sorts array using a custom comparator |
| hof_exists | Determine Whether Some Element Exists in an Array Column |
| hof_filter | Filter Array Column |
| hof_forall | Checks whether all elements in an array satisfy a predicate |
| hof_map_filter | Filters a map |
| hof_map_zip_with | Merges two maps into one |
| hof_transform | Transform Array Column |
| hof_transform_keys | Transforms keys of a map |
| hof_transform_values | Transforms values of a map |
| hof_zip_with | Combines 2 Array Columns |
| inner_join | Inner join |
| invoke | Invoke a Method on a JVM Object |
| invoke_method | Generic Call Interface |
| jarray | Instantiate a Java array with a specific element type. |
| jfloat | Instantiate a Java float type. |
| jfloat_array | Instantiate an Array[Float]. |
| j_invoke | Invoke a Java function. |
| j_invoke_method | Generic Call Interface |
| jobj_class | Superclasses of object |
| jobj_set_param | Parameter Setting for JVM Objects |
| join.tbl_spark | Join Spark tbls. |
| left_join | Left join |
| list_sparklyr_jars | list all sparklyr-*.jar files that have been built |
| livy_config | Create a Spark Configuration for Livy |
| livy_install | Install Livy |
| livy_service | Start Livy |
| ml_add_stage | Add a Stage to a Pipeline |
| ml_aft_survival_regression | Spark ML - Survival Regression |
| ml_als | Spark ML - ALS |
| ml_als_tidiers | Tidying methods for Spark ML ALS |
| ml_bisecting_kmeans | Spark ML - Bisecting K-Means Clustering |
| ml_call_constructor | Wrap a Spark ML JVM object |
| ml_chisquare_test | Chi-square hypothesis testing for categorical data. |
| ml_clustering_evaluator | Spark ML - Clustering Evaluator |
| ml-constructors | Constructors for Pipeline Stages |
| ml_corr | Compute correlation matrix |
| ml_decision_tree | Spark ML - Decision Trees |
| ml_default_stop_words | Default stop words |
| ml_evaluate | Evaluate the Model on a Validation Set |
| ml_evaluator | Spark ML - Evaluators |
| ml_feature_importances | Spark ML - Feature Importance for Tree Models |
| ml_fpgrowth | Frequent Pattern Mining - FPGrowth |
| ml_gaussian_mixture | Spark ML - Gaussian Mixture clustering. |
| ml_generalized_linear_regression | Spark ML - Generalized Linear Regression |
| ml_glm_tidiers | Tidying methods for Spark ML linear models |
| ml_gradient_boosted_trees | Spark ML - Gradient Boosted Trees |
| ml_isotonic_regression | Spark ML - Isotonic Regression |
| ml_isotonic_regression_tidiers | Tidying methods for Spark ML Isotonic Regression |
| ml_kmeans | Spark ML - K-Means Clustering |
| ml_kmeans_cluster_eval | Evaluate a K-mean clustering |
| ml_lda | Spark ML - Latent Dirichlet Allocation |
| ml_lda_tidiers | Tidying methods for Spark ML LDA models |
| ml_linear_regression | Spark ML - Linear Regression |
| ml_linear_svc | Spark ML - LinearSVC |
| ml_linear_svc_tidiers | Tidying methods for Spark ML linear svc |
| ml_logistic_regression | Spark ML - Logistic Regression |
| ml_logistic_regression_tidiers | Tidying methods for Spark ML Logistic Regression |
| ml_metrics_binary | Extracts metrics from a fitted table |
| ml_metrics_multiclass | Extracts metrics from a fitted table |
| ml_metrics_regression | Extracts metrics from a fitted table |
| ml-model-constructors | Constructors for 'ml_model' Objects |
| ml_model_data | Extracts data associated with a Spark ML model |
| ml_multilayer_perceptron_classifier | Spark ML - Multilayer Perceptron |
| ml_multilayer_perceptron_tidiers | Tidying methods for Spark ML MLP |
| ml_naive_bayes | Spark ML - Naive-Bayes |
| ml_naive_bayes_tidiers | Tidying methods for Spark ML Naive Bayes |
| ml_one_vs_rest | Spark ML - OneVsRest |
| ml-params | Spark ML - ML Params |
| ml_pca_tidiers | Tidying methods for Spark ML Principal Component Analysis |
| ml-persistence | Spark ML - Model Persistence |
| ml_pipeline | Spark ML - Pipelines |
| ml_power_iteration | Spark ML - Power Iteration Clustering |
| ml_prefixspan | Frequent Pattern Mining - PrefixSpan |
| ml_random_forest | Spark ML - Random Forest |
| ml_stage | Spark ML - Pipeline stage extraction |
| ml_standardize_formula | Standardize Formula Input for 'ml_model' |
| ml_summary | Spark ML - Extraction of summary metrics |
| ml_survival_regression_tidiers | Tidying methods for Spark ML Survival Regression |
| ml-transform-methods | Spark ML - Transform, fit, and predict methods (ml_... |
| ml_tree_tidiers | Tidying methods for Spark ML tree models |
| ml-tuning | Spark ML - Tuning |
| ml_uid | Spark ML - UID |
| ml_unsupervised_tidiers | Tidying methods for Spark ML unsupervised models |
| mutate | Mutate |
| na.replace | Replace Missing Values in Objects |
| nest | Nest |
| pipe | Pipe operator |
| pivot_longer | Pivot longer |
| pivot_wider | Pivot wider |
| print_jobj | Generic method for print jobj for a connection type |
| quote_sql_name | Translate input character vector or symbol to a SQL... |
| random_string | Random string generation |
| reactiveSpark | Reactive spark reader |
| reexports | Objects exported from other packages |
| registerDoSpark | Register a Parallel Backend |
| register_extension | Register a Package that Implements a Spark Extension |
| replace_na | Replace NA |
| right_join | Right join |
| sdf_along | Create DataFrame for along Object |
| sdf_bind | Bind multiple Spark DataFrames by row and column |
| sdf_broadcast | Broadcast hint |
| sdf_checkpoint | Checkpoint a Spark DataFrame |
| sdf_coalesce | Coalesces a Spark DataFrame |
| sdf_collect | Collect a Spark DataFrame into R. |
| sdf_copy_to | Copy an Object into Spark |
| sdf_crosstab | Cross Tabulation |
| sdf_debug_string | Debug Info for Spark DataFrame |
| sdf_describe | Compute summary statistics for columns of a data frame |
| sdf_dim | Support for Dimension Operations |
| sdf_distinct | Invoke distinct on a Spark DataFrame |
| sdf_drop_duplicates | Remove duplicates from a Spark DataFrame |
| sdf_expand_grid | Create a Spark dataframe containing all combinations of... |
| sdf_fast_bind_cols | Fast cbind for Spark DataFrames |
| sdf_from_avro | Convert column(s) from avro format |
| sdf_is_streaming | Spark DataFrame is Streaming |
| sdf_last_index | Returns the last index of a Spark DataFrame |
| sdf_len | Create DataFrame for Length |
| sdf_num_partitions | Gets number of partitions of a Spark DataFrame |
| sdf_partition_sizes | Compute the number of records within each partition of a... |
| sdf_persist | Persist a Spark DataFrame |
| sdf_pivot | Pivot a Spark DataFrame |
| sdf_project | Project features onto principal components |
| sdf_quantile | Compute (Approximate) Quantiles with a Spark DataFrame |
| sdf_random_split | Partition a Spark Dataframe |
| sdf_rbeta | Generate random samples from a Beta distribution |
| sdf_rbinom | Generate random samples from a binomial distribution |
| sdf_rcauchy | Generate random samples from a Cauchy distribution |
| sdf_rchisq | Generate random samples from a chi-squared distribution |
| sdf_read_column | Read a Column from a Spark DataFrame |
| sdf_register | Register a Spark DataFrame |
| sdf_repartition | Repartition a Spark DataFrame |
| sdf_residuals | Model Residuals |
| sdf_rexp | Generate random samples from an exponential distribution |
| sdf_rgamma | Generate random samples from a Gamma distribution |
| sdf_rgeom | Generate random samples from a geometric distribution |
| sdf_rhyper | Generate random samples from a hypergeometric distribution |
| sdf_rlnorm | Generate random samples from a log normal distribution |
| sdf_rnorm | Generate random samples from the standard normal distribution |
| sdf_rpois | Generate random samples from a Poisson distribution |
| sdf_rt | Generate random samples from a t-distribution |
| sdf_runif | Generate random samples from the uniform distribution U(0,... |
| sdf_rweibull | Generate random samples from a Weibull distribution. |
| sdf_sample | Randomly Sample Rows from a Spark DataFrame |
| sdf-saveload | Save / Load a Spark DataFrame |
| sdf_schema | Read the Schema of a Spark DataFrame |
| sdf_separate_column | Separate a Vector Column into Scalar Columns |
| sdf_seq | Create DataFrame for Range |
| sdf_sort | Sort a Spark DataFrame |
| sdf_sql | Spark DataFrame from SQL |
| sdf_to_avro | Convert column(s) to avro format |
| sdf-transform-methods | Spark ML - Transform, fit, and predict methods (sdf_... |
| sdf_unnest_longer | Unnest longer |
| sdf_unnest_wider | Unnest wider |
| sdf_weighted_sample | Perform Weighted Random Sampling on a Spark DataFrame |
| sdf_with_sequential_id | Add a Sequential ID Column to a Spark DataFrame |
| sdf_with_unique_id | Add a Unique ID Column to a Spark DataFrame |
| select | Select |
| separate | Separate |
| spark_adaptive_query_execution | Retrieves or sets status of Spark AQE |
| spark_advisory_shuffle_partition_size | Retrieves or sets advisory size of the shuffle partition |
| spark-api | Access the Spark API |
| spark_apply | Apply an R Function in Spark |
| spark_apply_bundle | Create Bundle for Spark Apply |
| spark_apply_log | Log Writer for Spark Apply |
| spark_auto_broadcast_join_threshold | Retrieves or sets the auto broadcast join threshold |
| spark_coalesce_initial_num_partitions | Retrieves or sets initial number of shuffle partitions before... |
| spark_coalesce_min_num_partitions | Retrieves or sets the minimum number of shuffle partitions... |
| spark_coalesce_shuffle_partitions | Retrieves or sets whether coalescing contiguous shuffle... |
| spark_compilation_spec | Define a Spark Compilation Specification |
| spark_compile | Compile Scala sources into a Java Archive |
| spark_config | Read Spark Configuration |
| spark_config_exists | A helper function to check value exist under 'spark_config()' |
| spark_config_kubernetes | Kubernetes Configuration |
| spark_config_packages | Creates Spark Configuration |
| spark_config_settings | Retrieve Available Settings |
| spark_configuration | Runtime configuration interface for the Spark Session |
| spark_config_value | A helper function to retrieve values from 'spark_config()' |
| spark_connection | Retrieve the Spark Connection Associated with an R Object |
| spark_connection-class | spark_connection class |
| spark_connection_find | Find Spark Connection |
| spark-connections | Manage Spark Connections |
| spark_connect_method | Function that negotiates the connection with the Spark... |
| spark_context_config | Runtime configuration interface for the Spark Context. |
| spark_dataframe | Retrieve a Spark DataFrame |
| spark_default_compilation_spec | Default Compilation Specification for Spark Extensions |
| spark_default_version | determine the version that will be used by default if version... |
| spark_dependency | Define a Spark dependency |
| spark_dependency_fallback | Fallback to Spark Dependency |
| spark_extension | Create Spark Extension |
| spark_get_java | Find path to Java |
| spark_home_dir | Find the SPARK_HOME directory for a version of Spark |
| spark_home_set | Set the SPARK_HOME environment variable |
| spark_ide_connection_open | Set of functions to provide integration with the RStudio IDE |
| spark_insert_table | Inserts a Spark DataFrame into a Spark table |
| spark_install | Download and install various versions of Spark |
| spark_install_find | Find a given Spark installation by version. |
| spark_install_sync | helper function to sync sparkinstall project to sparklyr |
| spark_integ_test_skip | It lets the package know if it should test a particular... |
| spark_jobj | Retrieve a Spark JVM Object Reference |
| spark_jobj-class | spark_jobj class |
| spark_last_error | Surfaces the last error from Spark captured by internal... |
| spark_load_table | Reads from a Spark Table into a Spark DataFrame. |
| spark_log | View Entries in the Spark Log |
| sparklyr_get_backend_port | Return the port number of a 'sparklyr' backend. |
| spark_pipeline_stage | Create a Pipeline Stage Object |
| spark_read | Read file(s) into a Spark DataFrame using a custom reader |
| spark_read_avro | Read Apache Avro data into a Spark DataFrame. |
| spark_read_binary | Read binary data into a Spark DataFrame. |
| spark_read_csv | Read a CSV file into a Spark DataFrame |
| spark_read_delta | Read from Delta Lake into a Spark DataFrame. |
| spark_read_image | Read image data into a Spark DataFrame. |
| spark_read_jdbc | Read from JDBC connection into a Spark DataFrame. |
| spark_read_json | Read a JSON file into a Spark DataFrame |
| spark_read_libsvm | Read libsvm file into a Spark DataFrame. |
| spark_read_orc | Read a ORC file into a Spark DataFrame |
| spark_read_parquet | Read a Parquet file into a Spark DataFrame |
| spark_read_source | Read from a generic source into a Spark DataFrame. |
| spark_read_table | Reads from a Spark Table into a Spark DataFrame. |
| spark_read_text | Read a Text file into a Spark DataFrame |
| spark_save_table | Saves a Spark DataFrame as a Spark table |
| spark_statistical_routines | Generate random samples from some distribution |
| spark_table_name | Generate a Table Name from Expression |
| spark_version | Get the Spark Version Associated with a Spark Connection |
| spark_version_from_home | Get the Spark Version Associated with a Spark Installation |
| spark_versions | Retrieves a dataframe available Spark versions that van be... |
| spark_web | Open the Spark web interface |
| spark_write | Write Spark DataFrame to file using a custom writer |
| spark_write_avro | Serialize a Spark DataFrame into Apache Avro format |
| spark_write_csv | Write a Spark DataFrame to a CSV |
| spark_write_delta | Writes a Spark DataFrame into Delta Lake |
| spark_write_jdbc | Writes a Spark DataFrame into a JDBC table |
| spark_write_json | Write a Spark DataFrame to a JSON file |
| spark_write_orc | Write a Spark DataFrame to a ORC file |
| spark_write_parquet | Write a Spark DataFrame to a Parquet file |
| spark_write_rds | Write Spark DataFrame to RDS files |
| spark_write_source | Writes a Spark DataFrame into a generic source |
| spark_write_table | Writes a Spark DataFrame into a Spark table |
| spark_write_text | Write a Spark DataFrame to a Text file |
| sql-transformer | Feature Transformation - SQLTransformer |
| src_databases | Show database list |
| stream_find | Find Stream |
| stream_generate_test | Generate Test Stream |
| stream_id | Spark Stream's Identifier |
| stream_lag | Apply lag function to columns of a Spark Streaming DataFrame |
| stream_name | Spark Stream's Name |
| stream_read_csv | Read files created by the stream |
| stream_render | Render Stream |
| stream_stats | Stream Statistics |
| stream_stop | Stops a Spark Stream |
| stream_trigger_continuous | Spark Stream Continuous Trigger |
| stream_trigger_interval | Spark Stream Interval Trigger |
| stream_view | View Stream |
| stream_watermark | Watermark Stream |
| stream_write_csv | Write files to the stream |
| stream_write_memory | Write Memory Stream |
| stream_write_table | Write Stream to Table |
| sub-.tbl_spark | Subsetting operator for Spark dataframe |
| tbl_cache | Cache a Spark Table |
| tbl_change_db | Use specific database |
| tbl_uncache | Uncache a Spark Table |
| transform_sdf | transform a subset of column(s) in a Spark Dataframe |
| unite | Unite |
| unnest | Unnest |
| worker_spark_apply_unbundle | Extracts a bundle of dependencies required by 'spark_apply()' |
