water.bindings.pojos.ParseSetupV3 Maven / Gradle / Ivy
/*
* This file is auto-generated by h2o-3/h2o-bindings/bin/gen_java.py
* Copyright 2016 H2O.ai; Apache License Version 2.0 (see LICENSE for details)
*/
package water.bindings.pojos;
import com.google.gson.Gson;
import com.google.gson.annotations.*;
public class ParseSetupV3 extends RequestSchemaV3 {
/**
* Source frames
*/
@SerializedName("source_frames")
public FrameKeyV3[] sourceFrames;
/**
* Parser type
*/
@SerializedName("parse_type")
public ApiParseTypeValuesProvider parseType;
/**
* Field separator
*/
public byte separator;
/**
* Single quotes
*/
@SerializedName("single_quotes")
public boolean singleQuotes;
/**
* Check header: 0 means guess, +1 means 1st line is header not data, -1 means 1st line is data not header
*/
@SerializedName("check_header")
public int checkHeader;
/**
* Column names
*/
@SerializedName("column_names")
public String[] columnNames;
/**
* Skipped columns indices
*/
@SerializedName("skipped_columns")
public int[] skippedColumns;
/**
* Value types for columns
*/
@SerializedName("column_types")
public String[] columnTypes;
/**
* NA strings for columns
*/
@SerializedName("na_strings")
public String[][] naStrings;
/**
* Regex for names of columns to return
*/
@SerializedName("column_name_filter")
public String columnNameFilter;
/**
* Column offset to return
*/
@SerializedName("column_offset")
public int columnOffset;
/**
* Number of columns to return
*/
@SerializedName("column_count")
public int columnCount;
/**
* Suggested name
*/
@SerializedName("destination_frame")
public String destinationFrame;
/**
* Number of header lines found
*/
@SerializedName("header_lines")
public long headerLines;
/**
* Number of columns
*/
@SerializedName("number_columns")
public int numberColumns;
/**
* Sample data
*/
public String[][] data;
/**
* Warnings
*/
public String[] warnings;
/**
* Size of individual parse tasks
*/
@SerializedName("chunk_size")
public int chunkSize;
/**
* Total number of columns we would return with no column pagination
*/
@SerializedName("total_filtered_column_count")
public int totalFilteredColumnCount;
/**
* Custom characters to be treated as non-data line markers
*/
@SerializedName("custom_non_data_line_markers")
public String customNonDataLineMarkers;
/**
* Key-reference to an initialized instance of a Decryption Tool
*/
@SerializedName("decrypt_tool")
public DecryptionToolKeyV3 decryptTool;
/**
* Names of the columns the persisted dataset has been partitioned by.
*/
@SerializedName("partition_by")
public String[] partitionBy;
/**
* One ASCII character used to escape other characters.
*/
public byte escapechar;
/**
* If true, will force the column types to be either the ones in Parquet schema for Parquet files or the ones
* specified in column_types. This parameter is used for numerical columns only. Other column settings will happen
* without setting this parameter. Defaults to false.
*/
@SerializedName("force_col_types")
public boolean forceColTypes;
/*------------------------------------------------------------------------------------------------------------------
// INHERITED
//------------------------------------------------------------------------------------------------------------------
// Comma-separated list of JSON field paths to exclude from the result, used like:
// "/3/Frames?_exclude_fields=frames/frame_id/URL,__meta"
public String _excludeFields;
*/
/**
* Public constructor
*/
public ParseSetupV3() {
parseType = ApiParseTypeValuesProvider.GUESS;
separator = 0;
singleQuotes = false;
checkHeader = 0;
columnNameFilter = "";
columnOffset = 0;
columnCount = 0;
destinationFrame = "";
headerLines = 0L;
numberColumns = 0;
chunkSize = 4194304;
totalFilteredColumnCount = 0;
customNonDataLineMarkers = "";
escapechar = 0;
forceColTypes = false;
_excludeFields = "";
}
/**
* Return the contents of this object as a JSON String.
*/
@Override
public String toString() {
return new Gson().toJson(this);
}
}