Uses of Class com.snowflake.snowpark_java.DataFrame (Snowpark Java API Reference 1.15.0)

Packages that use DataFrame
Package Description

com.snowflake.snowpark_java
Provides most of the classes for the Snowpark Java API.

Packages that use DataFrame
Package	Description
com.snowflake.snowpark_java	Provides most of the classes for the Snowpark Java API.

Uses of DataFrame in com.snowflake.snowpark_java

Subclasses of DataFrame in com.snowflake.snowpark_java
Modifier and Type	Class	Description
`class`	`CopyableDataFrame`	DataFrame for loading data from files in a stage to a table.
`class`	`HasCachedResult`	A DataFrame that returns cached data.
`class`	`Updatable`	Represents a lazily-evaluated Updatable.

Methods in com.snowflake.snowpark_java that return DataFrame
Modifier and Type	Method	Description
`DataFrame`	DataFrame.`agg(Column... exprs)`	Aggregate the data in the DataFrame.
`DataFrame`	RelationalGroupedDataFrame.`agg(Column... cols)`	Returns a DataFrame with aggregated computed according to the supplied Column expressions.
`DataFrame`	DataFrame.`alias(String alias)`	Returns the current DataFrame aliased as the input alias name.
`DataFrame`	RelationalGroupedDataFrame.`any_value(Column... cols)`	Returns non-deterministic values for the specified columns.
`DataFrame`	RelationalGroupedDataFrame.`avg(Column... cols)`	Return the average for the specified numeric columns.
`DataFrame`	RelationalGroupedDataFrame.`builtin(String aggName, Column... cols)`	Computes the builtin aggregate 'aggName' over the specified columns.
`DataFrame`	DataFrame.`clone()`	Returns a clone of this DataFrame.
`DataFrame`	RelationalGroupedDataFrame.`count()`	Return the number of rows for each group.
`DataFrame`	Session.`createDataFrame(Row[] data, StructType schema)`	Creates a new DataFrame that uses the specified schema and contains the specified Row objects.
`DataFrame`	DataFrame.`crossJoin(DataFrame right)`	Performs a cross join, which returns the cartesian product of the current DataFrame and another DataFrame (`right`).
`DataFrame`	DataFrameStatFunctions.`crosstab(String col1, String col2)`	Computes a pair-wise frequency table (a ''contingency table'') for the specified columns.
`DataFrame`	DataFrame.`distinct()`	Returns a new DataFrame that contains only the rows with distinct values from the current DataFrame.
`DataFrame`	DataFrame.`drop(Column... columns)`	Returns a new DataFrame that excludes the columns with the specified names from the output.
`DataFrame`	DataFrame.`drop(String... columnNames)`	Returns a new DataFrame that excludes the columns with the specified names from the output.
`DataFrame`	DataFrameNaFunctions.`drop(int minNonNullsPerRow, String[] cols)`	Returns a new DataFrame that excludes all rows containing fewer than `minNonNullsPerRow` non-null and non-NaN values in the specified columns `cols`.
`DataFrame`	DataFrame.`dropDuplicates(String... colNames)`	Creates a new DataFrame by removing duplicated rows on given subset of columns.
`DataFrame`	DataFrame.`except(DataFrame other)`	Returns a new DataFrame that contains all the rows from the current DataFrame except for the rows that also appear in another DataFrame (`other`).
`DataFrame`	DataFrameNaFunctions.`fill(Map<String,?> valueMap)`	Returns a new DataFrame that replaces all null and NaN values in the specified columns with the values provided.
`DataFrame`	DataFrame.`filter(Column condition)`	Filters rows based on the specified conditional expression (similar to WHERE in SQL).
`DataFrame`	DataFrame.`flatten(Column input)`	Flattens (explodes) compound values into multiple rows (similar to the SQL FLATTEN
`DataFrame`	DataFrame.`flatten(Column input, String path, boolean outer, boolean recursive, String mode)`	Flattens (explodes) compound values into multiple rows (similar to the SQL FLATTEN
`DataFrame`	Session.`flatten(Column input)`	Creates a new DataFrame by flattening compound values into multiple rows.
`DataFrame`	Session.`flatten(Column input, String path, boolean outer, boolean recursive, String mode)`	Creates a new DataFrame by flattening compound values into multiple rows.
`DataFrame`	Session.`generator(long rowCount, Column... columns)`	Creates a new DataFrame via Generator function.
`DataFrame`	DataFrame.`intersect(DataFrame other)`	Returns a new DataFrame that contains the intersection of rows from the current DataFrame and another DataFrame (`other`).
`DataFrame`	DataFrame.`join(Column func)`	Joins the current DataFrame with the output of the specified table function `func`.
`DataFrame`	DataFrame.`join(Column func, Column[] partitionBy, Column[] orderBy)`	Joins the current DataFrame with the output of the specified table function `func`.
`DataFrame`	DataFrame.`join(DataFrame right)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`).
`DataFrame`	DataFrame.`join(DataFrame right, Column joinExpr)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`) using the join condition specified in an expression (`joinExpr`).
`DataFrame`	DataFrame.`join(DataFrame right, Column joinExpr, String joinType)`	Performs a join of the specified type (`joinType`) with the current DataFrame and another DataFrame (`right`) using the join condition specified in an expression (`joinExpr`).
`DataFrame`	DataFrame.`join(DataFrame right, String usingColumn)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`) on a column (`usingColumn`).
`DataFrame`	DataFrame.`join(DataFrame right, String[] usingColumns)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`) on a list of columns (`usingColumns`).
`DataFrame`	DataFrame.`join(DataFrame right, String[] usingColumns, String joinType)`	Performs a join of the specified type (`joinType`) with the current DataFrame and another DataFrame (`right`) on a list of columns (`usingColumns`).
`DataFrame`	DataFrame.`join(TableFunction func, Column... args)`	Joins the current DataFrame with the output of the specified table function `func`.
`DataFrame`	DataFrame.`join(TableFunction func, Column[] args, Column[] partitionBy, Column[] orderBy)`	Joins the current DataFrame with the output of the specified user-defined table function (UDTF) `func`.
`DataFrame`	DataFrame.`join(TableFunction func, Map<String,Column> args)`	Joins the current DataFrame with the output of the specified table function `func` that takes named parameters (e.g.
`DataFrame`	DataFrame.`join(TableFunction func, Map<String,Column> args, Column[] partitionBy, Column[] orderBy)`	Joins the current DataFrame with the output of the specified user-defined table function (UDTF) `func`.
`DataFrame`	DataFrame.`limit(int n)`	Returns a new DataFrame that contains at most `n` rows from the current DataFrame (similar to LIMIT in SQL).
`DataFrame`	RelationalGroupedDataFrame.`max(Column... cols)`	Return the max for the specified numeric columns.
`DataFrame`	RelationalGroupedDataFrame.`mean(Column... cols)`	Return the average for the specified numeric columns.
`DataFrame`	RelationalGroupedDataFrame.`median(Column... cols)`	Return the median for the specified numeric columns.
`DataFrame`	RelationalGroupedDataFrame.`min(Column... cols)`	Return the min for the specified numeric columns.
`DataFrame`	DataFrame.`naturalJoin(DataFrame right)`	Performs a natural join (a default inner join) of the current DataFrame and another DataFrame (`right`).
`DataFrame`	DataFrame.`naturalJoin(DataFrame right, String joinType)`	Performs a natural join of the specified type (`joinType`) with the current DataFrame and another DataFrame (`right`).
`DataFrame[]`	DataFrame.`randomSplit(double[] weights)`	Randomly splits the current DataFrame into separate DataFrames, using the specified weights.
`DataFrame`	Session.`range(long end)`	Creates a new DataFrame from a range of numbers starting from 0.
`DataFrame`	Session.`range(long start, long end)`	Creates a new DataFrame from a range of numbers.
`DataFrame`	Session.`range(long start, long end, long step)`	Creates a new DataFrame from a range of numbers.
`DataFrame`	DataFrame.`rename(String newName, Column col)`	Returns a DataFrame with the specified column `col` renamed as `newName`.
`DataFrame`	DataFrameNaFunctions.`replace(String colName, Map<?,?> replacement)`	Returns a new DataFrame that replaces values in a specified column.
`DataFrame`	DataFrame.`sample(double probabilityFraction)`	Returns a new DataFrame that contains a sampling of rows from the current DataFrame.
`DataFrame`	DataFrame.`sample(long num)`	Returns a new DataFrame with a sample of N rows from the underlying DataFrame.
`DataFrame`	DataFrameStatFunctions.`sampleBy(Column col, Map<?,Double> fractions)`	Returns a DataFrame containing a stratified sample without replacement, based on a Map that specifies the fraction for each stratum.
`DataFrame`	DataFrameStatFunctions.`sampleBy(String colName, Map<?,Double> fractions)`	Returns a DataFrame containing a stratified sample without replacement, based on a Map that specifies the fraction for each stratum.
`DataFrame`	DataFrame.`select(Column... columns)`	Generates a new DataFrame with the specified Column expressions as output (similar to SELECT in SQL).
`DataFrame`	DataFrame.`select(String... columnNames)`	Returns a new DataFrame with a subset of named columns (similar to SELECT in SQL).
`DataFrame`	DataFrame.`sort(Column... sortExprs)`	Sorts a DataFrame by the specified expressions (similar to ORDER BY in SQL).
`DataFrame`	Session.`sql(String query)`	Returns a new `DataFrame` representing the results of a SQL query.
`DataFrame`	Session.`sql(String query, Object... params)`	Returns a new `DataFrame` representing the results of a SQL query.
`DataFrame`	Session.`storedProcedure(StoredProcedure sp, Object... args)`	Creates a new DataFrame from the given Stored Procedure and arguments.
`DataFrame`	Session.`storedProcedure(String spName, Object... args)`	Creates a new DataFrame from the given Stored Procedure and arguments.
`DataFrame`	RelationalGroupedDataFrame.`sum(Column... cols)`	Return the sum for the specified numeric columns.
`DataFrame`	DataFrameReader.`table(String name)`	Returns a DataFrame that is set up to load data from the specified table.
`DataFrame`	Session.`tableFunction(Column func)`	Creates a new DataFrame from the given table function and arguments.
`DataFrame`	Session.`tableFunction(TableFunction func, Column... args)`	Creates a new DataFrame from the given table function and arguments.
`DataFrame`	Session.`tableFunction(TableFunction func, Map<String,Column> args)`	Creates a new DataFrame from the given table function and arguments.
`DataFrame`	DataFrame.`toDF(String... colNames)`	Creates a new DataFrame containing the data in the current DataFrame but in columns with the specified names.
`DataFrame`	DataFrame.`union(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), excluding any duplicate rows.
`DataFrame`	DataFrame.`unionAll(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), including any duplicate rows.
`DataFrame`	DataFrame.`unionAllByName(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), including any duplicate rows.
`DataFrame`	DataFrame.`unionByName(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), excluding any duplicate rows.
`DataFrame`	DataFrame.`where(Column condition)`	Filters rows based on the specified conditional expression (similar to WHERE in SQL).
`DataFrame`	DataFrame.`withColumn(String colName, Column col)`	Returns a DataFrame with an additional column with the specified name (`colName`).
`DataFrame`	DataFrame.`withColumns(String[] colNames, Column[] values)`	Returns a DataFrame with additional columns with the specified names (`colNames`).

Methods in com.snowflake.snowpark_java with parameters of type DataFrame
Modifier and Type	Method	Description
`static Column`	Functions.`col(DataFrame df)`	Generates a Column representing the result of the input DataFrame.
`DataFrame`	DataFrame.`crossJoin(DataFrame right)`	Performs a cross join, which returns the cartesian product of the current DataFrame and another DataFrame (`right`).
`DeleteResult`	Updatable.`delete(Column condition, DataFrame sourceData)`	Deletes all rows in the updatable that satisfy specified condition where condition includes columns in other `DataFrame`, and returns a `DeleteResult`, representing number of rows deleted.
`TypedAsyncJob<DeleteResult>`	UpdatableAsyncActor.`delete(Column condition, DataFrame sourceData)`	Executes `Updatable.delete` asynchronously.
`DataFrame`	DataFrame.`except(DataFrame other)`	Returns a new DataFrame that contains all the rows from the current DataFrame except for the rows that also appear in another DataFrame (`other`).
`Column`	Column.`in(DataFrame df)`	Returns a conditional expression that you can pass to the filter or where method to perform a WHERE ...
`static Column`	Functions.`in(Column[] columns, DataFrame df)`	Returns a conditional expression that you can pass to the filter or where method to perform the equivalent of a WHERE ...
`DataFrame`	DataFrame.`intersect(DataFrame other)`	Returns a new DataFrame that contains the intersection of rows from the current DataFrame and another DataFrame (`other`).
`DataFrame`	DataFrame.`join(DataFrame right)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`).
`DataFrame`	DataFrame.`join(DataFrame right, Column joinExpr)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`) using the join condition specified in an expression (`joinExpr`).
`DataFrame`	DataFrame.`join(DataFrame right, Column joinExpr, String joinType)`	Performs a join of the specified type (`joinType`) with the current DataFrame and another DataFrame (`right`) using the join condition specified in an expression (`joinExpr`).
`DataFrame`	DataFrame.`join(DataFrame right, String usingColumn)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`) on a column (`usingColumn`).
`DataFrame`	DataFrame.`join(DataFrame right, String[] usingColumns)`	Performs a default inner join of the current DataFrame and another DataFrame (`right`) on a list of columns (`usingColumns`).
`DataFrame`	DataFrame.`join(DataFrame right, String[] usingColumns, String joinType)`	Performs a join of the specified type (`joinType`) with the current DataFrame and another DataFrame (`right`) on a list of columns (`usingColumns`).
`MergeBuilder`	Updatable.`merge(DataFrame source, Column joinExpr)`	Initiates a merge action for this updatable with `DataFrame` source on specified join expression.
`DataFrame`	DataFrame.`naturalJoin(DataFrame right)`	Performs a natural join (a default inner join) of the current DataFrame and another DataFrame (`right`).
`DataFrame`	DataFrame.`naturalJoin(DataFrame right, String joinType)`	Performs a natural join of the specified type (`joinType`) with the current DataFrame and another DataFrame (`right`).
`static Column`	Functions.`toScalar(DataFrame df)`	Generates a Column representing the result of the input DataFrame.
`DataFrame`	DataFrame.`union(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), excluding any duplicate rows.
`DataFrame`	DataFrame.`unionAll(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), including any duplicate rows.
`DataFrame`	DataFrame.`unionAllByName(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), including any duplicate rows.
`DataFrame`	DataFrame.`unionByName(DataFrame other)`	Returns a new DataFrame that contains all the rows in the current DataFrame and another DataFrame (`other`), excluding any duplicate rows.
`UpdateResult`	Updatable.`update(Map<Column,Column> assignments, Column condition, DataFrame sourceData)`	Updates all rows in the updatable that satisfy specified condition where condition includes columns in other `DataFrame`, and returns a `UpdateResult`, representing number of rows modified and number of multi-joined rows modified.
`TypedAsyncJob<UpdateResult>`	UpdatableAsyncActor.`update(Map<Column,Column> assignments, Column condition, DataFrame sourceData)`	Executes `Updatable.update` asynchronously.
`UpdateResult`	Updatable.`updateColumn(Map<String,Column> assignments, Column condition, DataFrame sourceData)`	Updates all rows in the updatable that satisfy specified condition where condition includes columns in other `DataFrame`, and returns a `UpdateResult`, representing number of rows modified and number of multi-joined rows modified.
`TypedAsyncJob<UpdateResult>`	UpdatableAsyncActor.`updateColumn(Map<String,Column> assignments, Column condition, DataFrame sourceData)`	Executes `Updatable.update` asynchronously.

Uses of Classcom.snowflake.snowpark_java.DataFrame

Uses of DataFrame in com.snowflake.snowpark_java

Uses of Class
com.snowflake.snowpark_java.DataFrame