sql-transformer: Feature Transformation - SQLTransformer

In sparklyr: R Interface to Apache Spark

Feature Transformation – SQLTransformer

Description

Implements the transformations which are defined by SQL statement. Currently we only support SQL syntax like 'SELECT ... FROM __THIS__ ...' where '__THIS__' represents the underlying table of the input dataset. The select clause specifies the fields, constants, and expressions to display in the output, it can be any select clause that Spark SQL supports. Users can also use Spark SQL built-in function and UDFs to operate on these selected columns.

Usage

ft_sql_transformer(
  x,
  statement = NULL,
  uid = random_string("sql_transformer_"),
  ...
)

ft_dplyr_transformer(x, tbl, uid = random_string("dplyr_transformer_"), ...)

Arguments

x	A spark_connection, ml_pipeline, or a tbl_spark.
statement	A SQL statement.
uid	A character string used to uniquely identify the feature transformer.
...	Optional arguments; currently unused.
tbl	A tbl_spark generated using dplyr transformations.

Details

ft_dplyr_transformer() is mostly a wrapper around ft_sql_transformer() that takes a tbl_spark instead of a SQL statement. Internally, the ft_dplyr_transformer() extracts the dplyr transformations used to generate tbl as a SQL statement or a sampling operation. Note that only single-table dplyr verbs are supported and that the sdf_ family of functions are not.

Value

The object returned depends on the class of x. If it is a spark_connection, the function returns a ml_estimator or a ml_estimator object. If it is a ml_pipeline, it will return a pipeline with the transformer or estimator appended to it. If a tbl_spark, it will return a tbl_spark with the transformation applied to it.

See Also

Other feature transformers: ft_binarizer(), ft_bucketizer(), ft_chisq_selector(), ft_count_vectorizer(), ft_dct(), ft_elementwise_product(), ft_feature_hasher(), ft_hashing_tf(), ft_idf(), ft_imputer(), ft_index_to_string(), ft_interaction(), ft_lsh, ft_max_abs_scaler(), ft_min_max_scaler(), ft_ngram(), ft_normalizer(), ft_one_hot_encoder(), ft_one_hot_encoder_estimator(), ft_pca(), ft_polynomial_expansion(), ft_quantile_discretizer(), ft_r_formula(), ft_regex_tokenizer(), ft_robust_scaler(), ft_standard_scaler(), ft_stop_words_remover(), ft_string_indexer(), ft_tokenizer(), ft_vector_assembler(), ft_vector_indexer(), ft_vector_slicer(), ft_word2vec()

sparklyr documentation built on May 29, 2024, 2:58 a.m.