Table (cudfjni 0.14 API)

java.lang.Object
- ai.rapids.cudf.Table

All Implemented Interfaces:

AutoCloseable
```
public final class Table
extends Object
implements AutoCloseable
```
Class to represent a collection of ColumnVectors and operations that can be performed on them collectively. The refcount on the columns will be increased once they are passed in

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`static class`	`Table.AggregateOperation` Class representing aggregate operations
`static class`	`Table.OrderByArg`
`static class`	`Table.TableOperation`
`static class`	`Table.TestBuilder` Create a table on the GPU with data from the CPU.

Constructor Summary

Constructors
Constructor and Description

Table(ColumnVector... columns)
Table class makes a copy of the array of ColumnVectors passed to it.

Constructors
Constructor and Description
`Table(ColumnVector... columns)` Table class makes a copy of the array of `ColumnVector`s passed to it.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods Deprecated Methods
Modifier and Type	Method and Description
`static Table.OrderByArg`	`asc(int index)`
`static Table.OrderByArg`	`asc(int index, boolean isNullSmallest)`
`void`	`close()`
`static Table`	`concatenate(Table... tables)` Concatenate multiple tables together to form a single table.
`ContiguousTable[]`	`contiguousSplit(int... indices)` Split a table at given boundaries, but the result of each split has memory that is laid out in a contiguous range of memory.
`static Aggregate`	`count(int index)` Returns count aggregation with only valid values.
`static Aggregate`	`count(int index, boolean include_nulls)` Returns count aggregation
`static Table.OrderByArg`	`desc(int index)`
`static Table.OrderByArg`	`desc(int index, boolean isNullSmallest)`
`Table`	`filter(ColumnVector mask)` Filters this table using a column of boolean values as a mask, returning a new one.
`static Aggregate`	`first(int index, boolean includeNulls)` Returns first aggregation.
`ColumnVector`	`getColumn(int index)` Return the `ColumnVector` at the specified index.
`long`	`getDeviceMemorySize()` Returns the Device memory buffer size.
`int`	`getNumberOfColumns()`
`long`	`getRowCount()`
`Table.AggregateOperation`	`groupBy(GroupByOptions groupByOptions, int... indices)` Returns aggregate operations grouped by columns provided in indices
`Table.AggregateOperation`	`groupBy(int... indices)` Returns aggregate operations grouped by columns provided in indices null is considered as key while grouping.
`ColumnVector`	`interleaveColumns()` Interleave all columns into a single column.
`static Aggregate`	`last(int index, boolean includeNulls)` Returns last aggregation.
`ColumnVector`	`lowerBound(boolean[] areNullsSmallest, Table valueTable, boolean[] descFlags)` Given a sorted table return the lower bound.
`static Aggregate`	`max(int index)` Returns max aggregation.
`static Aggregate`	`mean(int index)` Returns mean aggregation.
`static Aggregate`	`median(int index)` Returns median aggregation.
`static Aggregate`	`min(int index)` Returns min aggregation.
`Table.TableOperation`	`onColumns(int... indices)`
`Table`	`orderBy(Table.OrderByArg... args)` Orders the table using the sortkeys returning a new allocated table.
`static Table`	`readCSV(Schema schema, byte[] buffer)` Read CSV formatted data using the default CSVOptions.
`static Table`	`readCSV(Schema schema, CSVOptions opts, byte[] buffer)` Read CSV formatted data.
`static Table`	`readCSV(Schema schema, CSVOptions opts, byte[] buffer, long offset, long len)` Read CSV formatted data.
`static Table`	`readCSV(Schema schema, CSVOptions opts, File path)` Read a CSV file.
`static Table`	`readCSV(Schema schema, CSVOptions opts, HostMemoryBuffer buffer, long offset, long len)` Read CSV formatted data.
`static Table`	`readCSV(Schema schema, File path)` Read a CSV file using the default CSVOptions.
`static Table`	`readORC(byte[] buffer)` Read ORC formatted data.
`static Table`	`readORC(File path)` Read a ORC file using the default ORCOptions.
`static Table`	`readORC(ORCOptions opts, byte[] buffer)` Read ORC formatted data.
`static Table`	`readORC(ORCOptions opts, byte[] buffer, long offset, long len)` Read ORC formatted data.
`static Table`	`readORC(ORCOptions opts, File path)` Read a ORC file.
`static Table`	`readORC(ORCOptions opts, HostMemoryBuffer buffer, long offset, long len)` Read ORC formatted data.
`static Table`	`readParquet(byte[] buffer)` Read parquet formatted data.
`static Table`	`readParquet(File path)` Read a Parquet file using the default ParquetOptions.
`static Table`	`readParquet(ParquetOptions opts, byte[] buffer)` Read parquet formatted data.
`static Table`	`readParquet(ParquetOptions opts, byte[] buffer, long offset, long len)` Read parquet formatted data.
`static Table`	`readParquet(ParquetOptions opts, File path)` Read a Parquet file.
`static Table`	`readParquet(ParquetOptions opts, HostMemoryBuffer buffer, long offset, long len)` Read parquet formatted data.
`PartitionedTable`	`roundRobinPartition(int numberOfPartitions, int startPartition)` Round-robin partition a table into the specified number of partitions.
`static Aggregate`	`sum(int index)` Returns sum aggregation.
`String`	`toString()`
`ColumnVector`	`upperBound(boolean[] areNullsSmallest, Table valueTable, boolean[] descFlags)` Given a sorted table return the upper bound.
`void`	`writeORC(File outputFile)` Deprecated. please use writeORCChunked instead
`void`	`writeORC(ORCWriterOptions options, File outputFile)` Deprecated. please use writeORCChunked instead
`static TableWriter`	`writeORCChunked(ORCWriterOptions options, File outputFile)` Get a table writer to write ORC data to a file.
`static TableWriter`	`writeORCChunked(ORCWriterOptions options, HostBufferConsumer consumer)` Get a table writer to write ORC data and handle each chunk with a callback.
`void`	`writeParquet(File outputFile)` Deprecated. please use writeParquetChunked instead
`void`	`writeParquet(ParquetWriterOptions options, File outputFile)` Deprecated. please use writeParquetChunked instead
`static TableWriter`	`writeParquetChunked(ParquetWriterOptions options, File outputFile)` Get a table writer to write parquet data to a file.
`static TableWriter`	`writeParquetChunked(ParquetWriterOptions options, HostBufferConsumer consumer)` Get a table writer to write parquet data and handle each chunk with a callback.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - Table
```
public Table(ColumnVector... columns)
```
    Table class makes a copy of the array of ColumnVectors passed to it. The class will decrease the refcount on itself and all its contents when closed and free resources if refcount is zero
    
    Parameters:
    
    columns - - Array of ColumnVectors
- Method Detail
  - getColumn
```
public ColumnVector getColumn(int index)
```
    Return the ColumnVector at the specified index. If you want to keep a reference to the column around past the life time of the table, you will need to increment the reference count on the column yourself.
  - getRowCount
```
public final long getRowCount()
```
  - getNumberOfColumns
```
public final int getNumberOfColumns()
```
  - close
```
public void close()
```
    Specified by:
    
    close in interface AutoCloseable
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - getDeviceMemorySize
```
public long getDeviceMemorySize()
```
    Returns the Device memory buffer size.
  - readCSV
```
public static Table readCSV(Schema schema,
                            File path)
```
    Read a CSV file using the default CSVOptions.
    
    Parameters:
    
    schema - the schema of the file. You may use Schema.INFERRED to infer the schema.
    
    path - the local file to read.
    
    Returns:
    
    the file parsed as a table on the GPU.
  - readCSV
```
public static Table readCSV(Schema schema,
                            CSVOptions opts,
                            File path)
```
    Read a CSV file.
    
    Parameters:
    
    schema - the schema of the file. You may use Schema.INFERRED to infer the schema.
    
    opts - various CSV parsing options.
    
    path - the local file to read.
    
    Returns:
    
    the file parsed as a table on the GPU.
  - readCSV
```
public static Table readCSV(Schema schema,
                            byte[] buffer)
```
    Read CSV formatted data using the default CSVOptions.
    
    Parameters:
    
    schema - the schema of the data. You may use Schema.INFERRED to infer the schema.
    
    buffer - raw UTF8 formatted bytes.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readCSV
```
public static Table readCSV(Schema schema,
                            CSVOptions opts,
                            byte[] buffer)
```
    Read CSV formatted data.
    
    Parameters:
    
    schema - the schema of the data. You may use Schema.INFERRED to infer the schema.
    
    opts - various CSV parsing options.
    
    buffer - raw UTF8 formatted bytes.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readCSV
```
public static Table readCSV(Schema schema,
                            CSVOptions opts,
                            byte[] buffer,
                            long offset,
                            long len)
```
    Read CSV formatted data.
    
    Parameters:
    
    schema - the schema of the data. You may use Schema.INFERRED to infer the schema.
    
    opts - various CSV parsing options.
    
    buffer - raw UTF8 formatted bytes.
    
    offset - the starting offset into buffer.
    
    len - the number of bytes to parse.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readCSV
```
public static Table readCSV(Schema schema,
                            CSVOptions opts,
                            HostMemoryBuffer buffer,
                            long offset,
                            long len)
```
    Read CSV formatted data.
    
    Parameters:
    
    schema - the schema of the data. You may use Schema.INFERRED to infer the schema.
    
    opts - various CSV parsing options.
    
    buffer - raw UTF8 formatted bytes.
    
    offset - the starting offset into buffer.
    
    len - the number of bytes to parse.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readParquet
```
public static Table readParquet(File path)
```
    Read a Parquet file using the default ParquetOptions.
    
    Parameters:
    
    path - the local file to read.
    
    Returns:
    
    the file parsed as a table on the GPU.
  - readParquet
```
public static Table readParquet(ParquetOptions opts,
                                File path)
```
    Read a Parquet file.
    
    Parameters:
    
    opts - various parquet parsing options.
    
    path - the local file to read.
    
    Returns:
    
    the file parsed as a table on the GPU.
  - readParquet
```
public static Table readParquet(byte[] buffer)
```
    Read parquet formatted data.
    
    Parameters:
    
    buffer - raw parquet formatted bytes.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readParquet
```
public static Table readParquet(ParquetOptions opts,
                                byte[] buffer)
```
    Read parquet formatted data.
    
    Parameters:
    
    opts - various parquet parsing options.
    
    buffer - raw parquet formatted bytes.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readParquet
```
public static Table readParquet(ParquetOptions opts,
                                byte[] buffer,
                                long offset,
                                long len)
```
    Read parquet formatted data.
    
    Parameters:
    
    opts - various parquet parsing options.
    
    buffer - raw parquet formatted bytes.
    
    offset - the starting offset into buffer.
    
    len - the number of bytes to parse.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readParquet
```
public static Table readParquet(ParquetOptions opts,
                                HostMemoryBuffer buffer,
                                long offset,
                                long len)
```
    Read parquet formatted data.
    
    Parameters:
    
    opts - various parquet parsing options.
    
    buffer - raw parquet formatted bytes.
    
    offset - the starting offset into buffer.
    
    len - the number of bytes to parse.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readORC
```
public static Table readORC(File path)
```
    Read a ORC file using the default ORCOptions.
    
    Parameters:
    
    path - the local file to read.
    
    Returns:
    
    the file parsed as a table on the GPU.
  - readORC
```
public static Table readORC(ORCOptions opts,
                            File path)
```
    Read a ORC file.
    
    Parameters:
    
    opts - ORC parsing options.
    
    path - the local file to read.
    
    Returns:
    
    the file parsed as a table on the GPU.
  - readORC
```
public static Table readORC(byte[] buffer)
```
    Read ORC formatted data.
    
    Parameters:
    
    buffer - raw ORC formatted bytes.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readORC
```
public static Table readORC(ORCOptions opts,
                            byte[] buffer)
```
    Read ORC formatted data.
    
    Parameters:
    
    opts - various ORC parsing options.
    
    buffer - raw ORC formatted bytes.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readORC
```
public static Table readORC(ORCOptions opts,
                            byte[] buffer,
                            long offset,
                            long len)
```
    Read ORC formatted data.
    
    Parameters:
    
    opts - various ORC parsing options.
    
    buffer - raw ORC formatted bytes.
    
    offset - the starting offset into buffer.
    
    len - the number of bytes to parse.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - readORC
```
public static Table readORC(ORCOptions opts,
                            HostMemoryBuffer buffer,
                            long offset,
                            long len)
```
    Read ORC formatted data.
    
    Parameters:
    
    opts - various ORC parsing options.
    
    buffer - raw ORC formatted bytes.
    
    offset - the starting offset into buffer.
    
    len - the number of bytes to parse.
    
    Returns:
    
    the data parsed as a table on the GPU.
  - writeParquetChunked
```
public static TableWriter writeParquetChunked(ParquetWriterOptions options,
                                              File outputFile)
```
    Get a table writer to write parquet data to a file.
    
    Parameters:
    
    options - the parquet writer options.
    
    outputFile - where to write the file.
    
    Returns:
    
    a table writer to use for writing out multiple tables.
  - writeParquetChunked
```
public static TableWriter writeParquetChunked(ParquetWriterOptions options,
                                              HostBufferConsumer consumer)
```
    Get a table writer to write parquet data and handle each chunk with a callback.
    
    Parameters:
    
    options - the parquet writer options.
    
    consumer - a class that will be called when host buffers are ready with parquet formatted data in them.
    
    Returns:
    
    a table writer to use for writing out multiple tables.
  - writeParquet
```
@Deprecated
public void writeParquet(File outputFile)
```
    Deprecated. please use writeParquetChunked instead
    
    Writes this table to a Parquet file on the host
    
    Parameters:
    
    outputFile - file to write the table to
  - writeParquet
```
@Deprecated
public void writeParquet(ParquetWriterOptions options,
                                     File outputFile)
```
    Deprecated. please use writeParquetChunked instead
    
    Writes this table to a Parquet file on the host
    
    Parameters:
    
    options - parameters for the writer
    
    outputFile - file to write the table to
  - writeORCChunked
```
public static TableWriter writeORCChunked(ORCWriterOptions options,
                                          File outputFile)
```
    Get a table writer to write ORC data to a file.
    
    Parameters:
    
    options - the ORC writer options.
    
    outputFile - where to write the file.
    
    Returns:
    
    a table writer to use for writing out multiple tables.
  - writeORCChunked
```
public static TableWriter writeORCChunked(ORCWriterOptions options,
                                          HostBufferConsumer consumer)
```
    Get a table writer to write ORC data and handle each chunk with a callback.
    
    Parameters:
    
    options - the ORC writer options.
    
    consumer - a class that will be called when host buffers are ready with ORC formatted data in them.
    
    Returns:
    
    a table writer to use for writing out multiple tables.
  - writeORC
```
@Deprecated
public void writeORC(File outputFile)
```
    Deprecated. please use writeORCChunked instead
    
    Writes this table to a file on the host.
    
    Parameters:
    
    outputFile - - File to write the table to
  - writeORC
```
@Deprecated
public void writeORC(ORCWriterOptions options,
                                 File outputFile)
```
    Deprecated. please use writeORCChunked instead
    
    Writes this table to a file on the host.
    
    Parameters:
    
    outputFile - - File to write the table to
  - concatenate
```
public static Table concatenate(Table... tables)
```
    Concatenate multiple tables together to form a single table. The schema of each table (i.e.: number of columns and types of each column) must be equal across all tables and will determine the schema of the resulting table.
  - interleaveColumns
```
public ColumnVector interleaveColumns()
```
    Interleave all columns into a single column. Columns must all have the same data type and length. Example: ``` input = [[A1, A2, A3], [B1, B2, B3]] return = [A1, B1, A2, B2, A3, B3] ```
    
    Returns:
    
    The interleaved columns as a single column
  - lowerBound
```
public ColumnVector lowerBound(boolean[] areNullsSmallest,
                               Table valueTable,
                               boolean[] descFlags)
```
    Given a sorted table return the lower bound. Example: Single column: idx 0 1 2 3 4 inputTable = { 10, 20, 20, 30, 50 } valuesTable = { 20 } result = { 1 } Multi Column: idx 0 1 2 3 4 inputTable = {{ 10, 20, 20, 20, 20 }, { 5.0, .5, .5, .7, .7 }, { 90, 77, 78, 61, 61 }} valuesTable = {{ 20 }, { .7 }, { 61 }} result = { 3 } NaNs in column values produce incorrect results. The input table and the values table need to be non-empty (row count > 0) The column data types of the tables' have to match in order. Strings and String categories do not work for this method. If the input table is unsorted the results are wrong. Types of columns can be of mixed data types.
    
    Parameters:
    
    areNullsSmallest - true if nulls are assumed smallest
    
    valueTable - the table of values that need to be inserted
    
    descFlags - indicates the ordering of the column(s), true if descending
    
    Returns:
    
    ColumnVector with lower bound indices for all rows in valueTable
  - upperBound
```
public ColumnVector upperBound(boolean[] areNullsSmallest,
                               Table valueTable,
                               boolean[] descFlags)
```
    Given a sorted table return the upper bound. Example: Single column: idx 0 1 2 3 4 inputTable = { 10, 20, 20, 30, 50 } valuesTable = { 20 } result = { 3 } Multi Column: idx 0 1 2 3 4 inputTable = {{ 10, 20, 20, 20, 20 }, { 5.0, .5, .5, .7, .7 }, { 90, 77, 78, 61, 61 }} valuesTable = {{ 20 }, { .7 }, { 61 }} result = { 5 } NaNs in column values produce incorrect results. The input table and the values table need to be non-empty (row count > 0) The column data types of the tables' have to match in order. Strings and String categories do not work for this method. If the input table is unsorted the results are wrong. Types of columns can be of mixed data types.
    
    Parameters:
    
    areNullsSmallest - true if nulls are assumed smallest
    
    valueTable - the table of values that need to be inserted
    
    descFlags - indicates the ordering of the column(s), true if descending
    
    Returns:
    
    ColumnVector with upper bound indices for all rows in valueTable
  - orderBy
```
public Table orderBy(Table.OrderByArg... args)
```
    Orders the table using the sortkeys returning a new allocated table. The caller is responsible for cleaning up the ColumnVector returned as part of the output Table
    Example usage: orderBy(true, Table.asc(0), Table.desc(3)...);
    
    Parameters:
    
    args - - Suppliers to initialize sortKeys.
    
    Returns:
    
    Sorted Table
  - asc
```
public static Table.OrderByArg asc(int index)
```
  - desc
```
public static Table.OrderByArg desc(int index)
```
  - asc
```
public static Table.OrderByArg asc(int index,
                                   boolean isNullSmallest)
```
  - desc
```
public static Table.OrderByArg desc(int index,
                                    boolean isNullSmallest)
```
  - count
```
public static Aggregate count(int index)
```
    Returns count aggregation with only valid values. Null values are skipped.
    
    Parameters:
    
    index - Column on which aggregation is to be performed
    
    Returns:
    
    count aggregation of column `index` with null values skipped.
  - count
```
public static Aggregate count(int index,
                              boolean include_nulls)
```
    Returns count aggregation
    
    Parameters:
    
    index - Column on which aggregation is to be performed.
    
    include_nulls - Include nulls if set to true
    
    Returns:
    
    count aggregation of column `index`
  - max
```
public static Aggregate max(int index)
```
    Returns max aggregation. Null values are skipped.
    
    Parameters:
    
    index - Column on which max aggregation is to be performed.
    
    Returns:
    
    max aggregation of column `index`
  - min
```
public static Aggregate min(int index)
```
    Returns min aggregation. Null values are skipped.
    
    Parameters:
    
    index - Column on which min aggregation is to be performed.
    
    Returns:
    
    min aggregation of column `index`
  - sum
```
public static Aggregate sum(int index)
```
    Returns sum aggregation. Null values are skipped.
    
    Parameters:
    
    index - Column on which sum aggregation is to be performed.
    
    Returns:
    
    sum aggregation of column `index`
  - mean
```
public static Aggregate mean(int index)
```
    Returns mean aggregation. Null values are skipped.
    
    Parameters:
    
    index - Column on which mean aggregation is to be performed.
    
    Returns:
    
    mean aggregation of column `index`
  - median
```
public static Aggregate median(int index)
```
    Returns median aggregation. Null values are skipped.
    
    Parameters:
    
    index - Column on which median aggregation is to be performed.
    
    Returns:
    
    median aggregation of column `index`
  - first
```
public static Aggregate first(int index,
                              boolean includeNulls)
```
    Returns first aggregation.
    
    Parameters:
    
    index - Column on which first aggregation is to be performed.
    
    includeNulls - Specifies whether null values are included in the aggregate operation.
    
    Returns:
    
    first aggregation of column `index`
  - last
```
public static Aggregate last(int index,
                             boolean includeNulls)
```
    Returns last aggregation.
    
    Parameters:
    
    index - Column on which last aggregation is to be performed.
    
    includeNulls - Specifies whether null values are included in the aggregate operation.
    
    Returns:
    
    last aggregation of column `index`
  - groupBy
```
public Table.AggregateOperation groupBy(GroupByOptions groupByOptions,
                                        int... indices)
```
    Returns aggregate operations grouped by columns provided in indices
    
    Parameters:
    
    groupByOptions - Options provided in the builder
    
    indices - columnns to be considered for groupBy
  - groupBy
```
public Table.AggregateOperation groupBy(int... indices)
```
    Returns aggregate operations grouped by columns provided in indices null is considered as key while grouping.
    
    Parameters:
    
    indices - columnns to be considered for groupBy
  - roundRobinPartition
```
public PartitionedTable roundRobinPartition(int numberOfPartitions,
                                            int startPartition)
```
    Round-robin partition a table into the specified number of partitions. The first row is placed in the specified starting partition, the next row is placed in the next partition, and so on. When the last partition is reached then next partition is partition 0 and the algorithm continues until all rows have been placed in partitions, evenly distributing the rows among the partitions.
    
    Parameters:
    
    numberOfPartitions - - number of partitions to use
    
    startPartition - - starting partition index (i.e.: where first row is placed).
    
    Returns:
    
    - PartitionedTable - Table that exposes a limited functionality of the Table class
  - onColumns
```
public Table.TableOperation onColumns(int... indices)
```
  - filter
```
public Table filter(ColumnVector mask)
```
    Filters this table using a column of boolean values as a mask, returning a new one.
    Given a mask column, each element `i` from the input columns is copied to the output columns if the corresponding element `i` in the mask is non-null and `true`. This operation is stable: the input order is preserved.
    This table and mask columns must have the same number of rows.
    The output table has size equal to the number of elements in boolean_mask that are both non-null and `true`.
    If the original table row count is zero, there is no error, and an empty table is returned.
    
    Parameters:
    
    mask - column of type DType.BOOL8 used as a mask to filter the input column
    
    Returns:
    
    table containing copy of all elements of this table passing the filter defined by the boolean mask
  - contiguousSplit
```
public ContiguousTable[] contiguousSplit(int... indices)
```
    Split a table at given boundaries, but the result of each split has memory that is laid out in a contiguous range of memory. This allows for us to optimize copying the data in a single operation. Example: input: [{10, 12, 14, 16, 18, 20, 22, 24, 26, 28}, {50, 52, 54, 56, 58, 60, 62, 64, 66, 68}] splits: {2, 5, 9} output: [{{10, 12}, {14, 16, 18}, {20, 22, 24, 26}, {28}}, {{50, 52}, {54, 56, 58}, {60, 62, 64, 66}, {68}}]
    
    Parameters:
    
    indices - A vector of indices where to make the split
    
    Returns:
    
    The tables split at those points. NOTE: It is the responsibility of the caller to close the result. Each table and column holds a reference to the original buffer. But both the buffer and the table must be closed for the memory to be released.

Class Table

Nested Class Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Table

Method Detail

getColumn

getRowCount

getNumberOfColumns

close

toString

getDeviceMemorySize

readCSV

readCSV

readCSV

readCSV

readCSV

readCSV

readParquet

readParquet

readParquet

readParquet

readParquet

readParquet

readORC

readORC

readORC

readORC

readORC

readORC

writeParquetChunked

writeParquetChunked

writeParquet

writeParquet

writeORCChunked

writeORCChunked

writeORC

writeORC

concatenate

interleaveColumns

lowerBound

upperBound

orderBy

asc

desc

asc

desc

count

count

max

min

sum

mean

median

first

last

groupBy

groupBy

roundRobinPartition

onColumns

filter

contiguousSplit