DESCRIPTION

Type: Package
Package: sparklyr
Title: R Interface to Apache Spark
Version: 1.8.6
Authors@R:
    c(person(given = "Javier",
             family = "Luraschi",
             role = "aut",
             email = "jluraschi@gmail.com"),
      person(given = "Kevin",
             family = "Kuo",
             role = "aut",
             email = "kevin.kuo@rstudio.com",
             comment = c(ORCID = "0000-0001-7803-7901")),
      person(given = "Kevin",
             family = "Ushey",
             role = "aut",
             email = "kevin@rstudio.com"),
      person(given = "JJ",
             family = "Allaire",
             role = "aut",
             email = "jj@rstudio.com"),
      person(given = "Samuel",
             family = "Macedo",
             role = "ctb",
             email = "samuelmacedo@recife.ifpe.edu.br"),
      person(given = "Hossein",
             family = "Falaki",
             role = "aut",
             email = "hossein@databricks.com"),
      person(given = "Lu",
             family = "Wang",
             role = "aut",
             email = "lu.wang@databricks.com"),
      person(given = "Andy",
             family = "Zhang",
             role = "aut",
             email = "yue.zhang@databricks.com"),
      person(given = "Yitao",
             family = "Li",
             role = "aut",
             email = "yitaoli1990@gmail.com",
             comment = c(ORCID = "0000-0002-1261-905X")),
      person(given = "Jozef",
             family = "Hajnala",
             role = "ctb",
             email = "jozef.hajnala@gmail.com"),
      person(given = "Maciej",
             family = "Szymkiewicz",
             role = "ctb",
             email = "mszymkiewicz@gmail.com",
             comment = c(ORCID = "0000-0003-1469-9396")),
      person(given = "Wil",
             family = "Davis",
             role = "ctb",
             email = "william.davis@worthingtonindustries.com"),
      person(given = "Edgar",
             family = "Ruiz",
             role = c("aut", "cre"),
             email = "edgar@rstudio.com"),
      person(family = "RStudio",
             role = "cph"),
      person(family = "The Apache Software Foundation",
             role = c("aut", "cph")))
Maintainer: Edgar Ruiz <edgar@rstudio.com>
Description: R interface to Apache Spark, a fast and general
    engine for big data processing, see <https://spark.apache.org/>. This
    package supports connecting to local and remote Apache Spark clusters,
    provides a 'dplyr' compatible back-end, and provides an interface to
    Spark's built-in machine learning algorithms.
License: Apache License 2.0 | file LICENSE
URL: https://spark.posit.co/
BugReports: https://github.com/sparklyr/sparklyr/issues
Depends:
    R (>= 3.2)
Imports:
    config (>= 0.2),
    DBI (>= 1.0.0),
    dbplyr (>= 2.5.0),
    dplyr (>= 1.0.9),
    generics,
    globals,
    glue,
    httr (>= 1.2.1),
    jsonlite (>= 1.4),
    methods,
    openssl (>= 0.8),
    purrr,
    rlang (>= 0.1.4),
    rstudioapi (>= 0.10),
    tidyr (>= 1.2.0),
    tidyselect,
    uuid,
    vctrs,
    withr,
    xml2
Suggests:
    arrow (>= 0.17.0),
    broom,
    diffobj,
    foreach,
    ggplot2,
    iterators,
    janeaustenr,
    Lahman,
    mlbench,
    nnet,
    nycflights13,
    R6,
    r2d3,
    RCurl,
    reshape2,
    shiny (>= 1.0.1),
    parsnip,
    testthat,
    rprojroot
Encoding: UTF-8
RoxygenNote: 7.3.1
SystemRequirements: Spark: 2.x, or 3.x
Collate:
    'spark_data_build_types.R'
    'arrow_data.R'
    'spark_invoke.R'
    'browse_url.R'
    'spark_connection.R'
    'avro_utils.R'
    'config_settings.R'
    'config_spark.R'
    'connection_instances.R'
    'connection_progress.R'
    'connection_shinyapp.R'
    'spark_version.R'
    'connection_spark.R'
    'core_arrow.R'
    'core_config.R'
    'core_connection.R'
    'core_deserialize.R'
    'core_gateway.R'
    'core_invoke.R'
    'core_jobj.R'
    'core_serialize.R'
    'core_utils.R'
    'core_worker_config.R'
    'utils.R'
    'sql_utils.R'
    'data_copy.R'
    'data_csv.R'
    'spark_schema_from_rdd.R'
    'spark_apply_bundle.R'
    'spark_apply.R'
    'tables_spark.R'
    'tbl_spark.R'
    'spark_sql.R'
    'spark_dataframe.R'
    'dplyr_spark.R'
    'sdf_interface.R'
    'data_interface.R'
    'databricks_connection.R'
    'dbi_spark_connection.R'
    'dbi_spark_result.R'
    'dbi_spark_table.R'
    'do_spark.R'
    'dplyr_do.R'
    'dplyr_hof.R'
    'dplyr_join.R'
    'dplyr_spark_data.R'
    'dplyr_spark_table.R'
    'stratified_sample.R'
    'sdf_sql.R'
    'dplyr_sql.R'
    'dplyr_sql_translation.R'
    'dplyr_verbs.R'
    'imports.R'
    'install_spark.R'
    'install_spark_versions.R'
    'install_spark_windows.R'
    'install_tools.R'
    'java.R'
    'jobs_api.R'
    'kubernetes_config.R'
    'shell_connection.R'
    'livy_connection.R'
    'livy_install.R'
    'livy_invoke.R'
    'livy_service.R'
    'ml_clustering.R'
    'ml_classification_decision_tree_classifier.R'
    'ml_classification_gbt_classifier.R'
    'ml_classification_linear_svc.R'
    'ml_classification_logistic_regression.R'
    'ml_classification_multilayer_perceptron_classifier.R'
    'ml_classification_naive_bayes.R'
    'ml_classification_one_vs_rest.R'
    'ml_classification_random_forest_classifier.R'
    'ml_model_helpers.R'
    'ml_clustering_bisecting_kmeans.R'
    'ml_clustering_gaussian_mixture.R'
    'ml_clustering_kmeans.R'
    'ml_clustering_lda.R'
    'ml_clustering_power_iteration.R'
    'ml_constructor_utils.R'
    'ml_evaluate.R'
    'ml_evaluation_clustering.R'
    'ml_evaluation_prediction.R'
    'ml_evaluator.R'
    'ml_feature_binarizer.R'
    'ml_feature_bucketed_random_projection_lsh.R'
    'ml_feature_bucketizer.R'
    'ml_feature_chisq_selector.R'
    'ml_feature_count_vectorizer.R'
    'ml_feature_dct.R'
    'ml_feature_sql_transformer.R'
    'ml_feature_dplyr_transformer.R'
    'ml_feature_elementwise_product.R'
    'ml_feature_feature_hasher.R'
    'ml_feature_hashing_tf.R'
    'ml_feature_idf.R'
    'ml_feature_imputer.R'
    'ml_feature_index_to_string.R'
    'ml_feature_interaction.R'
    'ml_feature_lsh_utils.R'
    'ml_feature_max_abs_scaler.R'
    'ml_feature_min_max_scaler.R'
    'ml_feature_minhash_lsh.R'
    'ml_feature_ngram.R'
    'ml_feature_normalizer.R'
    'ml_feature_one_hot_encoder.R'
    'ml_feature_one_hot_encoder_estimator.R'
    'ml_feature_pca.R'
    'ml_feature_polynomial_expansion.R'
    'ml_feature_quantile_discretizer.R'
    'ml_feature_r_formula.R'
    'ml_feature_regex_tokenizer.R'
    'ml_feature_robust_scaler.R'
    'ml_feature_standard_scaler.R'
    'ml_feature_stop_words_remover.R'
    'ml_feature_string_indexer.R'
    'ml_feature_string_indexer_model.R'
    'ml_feature_tokenizer.R'
    'ml_feature_vector_assembler.R'
    'ml_feature_vector_indexer.R'
    'ml_feature_vector_slicer.R'
    'ml_feature_word2vec.R'
    'ml_fpm_fpgrowth.R'
    'ml_fpm_prefixspan.R'
    'ml_helpers.R'
    'ml_mapping_tables.R'
    'ml_metrics.R'
    'ml_model_als.R'
    'ml_model_bisecting_kmeans.R'
    'ml_model_constructors.R'
    'ml_model_decision_tree.R'
    'ml_model_gaussian_mixture.R'
    'ml_model_generalized_linear_regression.R'
    'ml_model_gradient_boosted_trees.R'
    'ml_model_isotonic_regression.R'
    'ml_model_kmeans.R'
    'ml_model_lda.R'
    'ml_model_linear_regression.R'
    'ml_model_linear_svc.R'
    'ml_model_logistic_regression.R'
    'ml_model_naive_bayes.R'
    'ml_model_one_vs_rest.R'
    'ml_model_random_forest.R'
    'ml_model_utils.R'
    'ml_param_utils.R'
    'ml_persistence.R'
    'ml_pipeline.R'
    'ml_pipeline_utils.R'
    'ml_print_utils.R'
    'ml_recommendation_als.R'
    'ml_regression_aft_survival_regression.R'
    'ml_regression_decision_tree_regressor.R'
    'ml_regression_gbt_regressor.R'
    'ml_regression_generalized_linear_regression.R'
    'ml_regression_isotonic_regression.R'
    'ml_regression_linear_regression.R'
    'ml_regression_random_forest_regressor.R'
    'ml_stat.R'
    'ml_summary.R'
    'ml_transformation_methods.R'
    'ml_transformer_and_estimator.R'
    'ml_tuning.R'
    'ml_tuning_cross_validator.R'
    'ml_tuning_train_validation_split.R'
    'ml_utils.R'
    'ml_validator_utils.R'
    'mutation.R'
    'na_actions.R'
    'new_model_multilayer_perceptron.R'
    'params_validator.R'
    'precondition.R'
    'project_template.R'
    'qubole_connection.R'
    'reexports.R'
    'sdf_dim.R'
    'sdf_distinct.R'
    'sdf_ml.R'
    'sdf_saveload.R'
    'sdf_sequence.R'
    'sdf_stat.R'
    'sdf_streaming.R'
    'tidyr_utils.R'
    'sdf_unnest_longer.R'
    'sdf_wrapper.R'
    'sdf_unnest_wider.R'
    'sdf_utils.R'
    'spark_compile.R'
    'spark_context_config.R'
    'spark_extensions.R'
    'spark_gateway.R'
    'spark_gen_embedded_sources.R'
    'spark_globals.R'
    'spark_hive.R'
    'spark_home.R'
    'spark_ide.R'
    'spark_submit.R'
    'spark_update_embedded_sources.R'
    'spark_utils.R'
    'spark_verify_embedded_sources.R'
    'stream_data.R'
    'stream_job.R'
    'stream_operations.R'
    'stream_shiny.R'
    'stream_view.R'
    'synapse_connection.R'
    'test_connection.R'
    'tidiers_ml_aft_survival_regression.R'
    'tidiers_ml_als.R'
    'tidiers_ml_isotonic_regression.R'
    'tidiers_ml_lda.R'
    'tidiers_ml_linear_models.R'
    'tidiers_ml_logistic_regression.R'
    'tidiers_ml_multilayer_perceptron.R'
    'tidiers_ml_naive_bayes.R'
    'tidiers_ml_svc_models.R'
    'tidiers_ml_tree_models.R'
    'tidiers_ml_unsupervised_models.R'
    'tidiers_pca.R'
    'tidiers_utils.R'
    'tidyr_fill.R'
    'tidyr_nest.R'
    'tidyr_pivot_utils.R'
    'tidyr_pivot_longer.R'
    'tidyr_pivot_wider.R'
    'tidyr_separate.R'
    'tidyr_unite.R'
    'tidyr_unnest.R'
    'worker_apply.R'
    'worker_connect.R'
    'worker_connection.R'
    'worker_invoke.R'
    'worker_log.R'
    'worker_main.R'
    'yarn_cluster.R'
    'yarn_config.R'
    'yarn_ui.R'
    'zzz.R'