water.api.FrameV3 Maven / Gradle / Ivy
package water.api;
import water.Futures;
import water.Key;
import water.MemoryManager;
import water.api.KeyV3.FrameKeyV3;
import water.fvec.*;
import water.fvec.Frame.VecSpecifier;
import water.parser.BufferedString;
import water.util.*;
/**
* All the details on a Frame. Note that inside ColV3 there are fields which won't be
* populated if we don't compute rollups, e.g. via
* the REST API endpoint /Frames//columns//summary.
*/
public class FrameV3 extends FrameBase {
// Input fields
@API(help="Row offset to display",direction=API.Direction.INPUT)
public long row_offset;
@API(help="Number of rows to display",direction=API.Direction.INOUT)
public int row_count;
@API(help="Column offset to return", direction=API.Direction.INOUT)
public int column_offset;
@API(help="Number of columns to return", direction=API.Direction.INOUT)
public int column_count;
@API(help="Total number of columns in the Frame", direction=API.Direction.INOUT)
public int total_column_count;
// Output fields
@API(help="checksum", direction=API.Direction.OUTPUT)
public long checksum;
@API(help="Number of rows in the Frame", direction=API.Direction.OUTPUT)
public long rows;
@API(help="Number of columns in the Frame", direction=API.Direction.OUTPUT)
public long num_columns;
@API(help="Default percentiles, from 0 to 1", direction=API.Direction.OUTPUT)
public double[] default_percentiles;
@API(help="Columns in the Frame", direction=API.Direction.OUTPUT)
public ColV3[] columns;
@API(help="Compatible models, if requested", direction=API.Direction.OUTPUT)
public String[] compatible_models;
@API(help="Chunk summary", direction=API.Direction.OUTPUT)
public TwoDimTableBase chunk_summary;
@API(help="Distribution summary", direction=API.Direction.OUTPUT)
public TwoDimTableBase distribution_summary;
public static class ColSpecifierV3 extends Schema {
public ColSpecifierV3() { }
public ColSpecifierV3(String column_name) {
this.column_name = column_name;
}
@API(help="Name of the column", direction= API.Direction.INOUT)
public String column_name;
@API(help="List of fields which specify columns that must contain this column", direction= API.Direction.INOUT)
public String[] is_member_of_frames;
}
public static class ColV3 extends Schema {
public ColV3() {}
@API(help="label", direction=API.Direction.OUTPUT)
public String label;
@API(help="missing", direction=API.Direction.OUTPUT)
public long missing_count;
@API(help="zeros", direction=API.Direction.OUTPUT)
public long zero_count;
@API(help="positive infinities", direction=API.Direction.OUTPUT)
public long positive_infinity_count;
@API(help="negative infinities", direction=API.Direction.OUTPUT)
public long negative_infinity_count;
@API(help="mins", direction=API.Direction.OUTPUT)
public double[] mins;
@API(help="maxs", direction=API.Direction.OUTPUT)
public double[] maxs;
@API(help="mean", direction=API.Direction.OUTPUT)
public double mean;
@API(help="sigma", direction=API.Direction.OUTPUT)
public double sigma;
@API(help="datatype: {enum, string, int, real, time, uuid}", direction=API.Direction.OUTPUT)
public String type;
@API(help="domain; not-null for categorical columns only", direction=API.Direction.OUTPUT)
public String[] domain;
@API(help="cardinality of this column's domain; not-null for categorical columns only", direction=API.Direction.OUTPUT)
public int domain_cardinality;
@API(help="data", direction=API.Direction.OUTPUT)
public double[] data;
@API(help="string data", direction=API.Direction.OUTPUT)
public String[] string_data;
@API(help="decimal precision, -1 for all digits", direction=API.Direction.OUTPUT)
public byte precision;
@API(help="Histogram bins; null if not computed", direction=API.Direction.OUTPUT)
public long[] histogram_bins;
@API(help="Start of histogram bin zero", direction=API.Direction.OUTPUT)
public double histogram_base;
@API(help="Stride per bin", direction=API.Direction.OUTPUT)
public double histogram_stride;
@API(help="Percentile values, matching the default percentiles", direction=API.Direction.OUTPUT)
public double[] percentiles;
transient Vec _vec;
ColV3(String name, Vec vec, long off, int len) {
label=name;
missing_count = vec.naCnt();
zero_count = vec.length() - vec.nzCnt() - missing_count;
positive_infinity_count = vec.pinfs();
negative_infinity_count = vec.ninfs();
mins = vec.mins();
maxs = vec.maxs();
mean = vec.mean();
sigma = vec.sigma();
// Histogram data is only computed on-demand. By default here we do NOT
// compute it, but will return any prior computed & cached histogram.
histogram_bins = vec.lazy_bins();
histogram_base = histogram_bins ==null ? 0 : vec.base();
histogram_stride= histogram_bins ==null ? 0 : vec.stride();
percentiles = histogram_bins ==null ? null : vec.pctiles();
type = vec.isCategorical() ? "enum" : vec.isUUID() ? "uuid" : vec.isString() ? "string" : (vec.isInt() ? (vec.isTime() ? "time" : "int") : "real");
domain = vec.domain();
if (vec.isCategorical()) {
domain_cardinality = domain.length;
} else {
domain_cardinality = 0;
}
len = (int)Math.min(len,vec.length()-off);
if( vec.isUUID() ) {
string_data = new String[len];
for (int i = 0; i < len; i++)
string_data[i] = vec.isNA(off + i) ? null : PrettyPrint.UUID(vec.at16l(off + i), vec.at16h(off + i));
data = null;
} else if ( vec.isString() ) {
string_data = new String[len];
BufferedString tmpStr = new BufferedString();
for (int i = 0; i < len; i++)
string_data[i] = vec.isNA(off + i) ? null : vec.atStr(tmpStr,off + i).toString();
data = null;
} else {
data = MemoryManager.malloc8d(len);
for( int i=0; i 0) // len == 0 is presumed to be a header file
precision = vec.chunkForRow(0).precision();
}
public void clearBinsField() {
this.histogram_bins = null;
}
}
public FrameV3() { super(); }
/* Key-only constructor, for the times we only want to return the key. */
FrameV3(Key frame_id) { this.frame_id = new FrameKeyV3(frame_id); }
FrameV3(Frame fr) {
this(fr, 1, (int) fr.numRows(), 0, 0); // NOTE: possible row len truncation
}
FrameV3(Frame f, long row_offset, int row_count) {
this(f, row_offset, row_count, 0, 0);
}
FrameV3(Frame f, long row_offset, int row_count, int column_offset, int column_count) {
this.fillFromImpl(f, row_offset, row_count, column_offset, column_count);
}
@Override public FrameV3 fillFromImpl(Frame f) {
return fillFromImpl(f, 1, (int)f.numRows(), 0, 0);
}
public FrameV3 fillFromImpl(Frame f, long row_offset, int row_count, int column_offset, int column_count) {
if( row_count == 0 ) row_count = 100; // 100 rows by default
if( column_count == 0 ) column_count = f.numCols() - column_offset; // full width by default
row_count = (int) Math.min( row_count, row_offset + f.numRows());
column_count = (int) Math.min(column_count, column_offset + f.numCols());
this.frame_id = new FrameKeyV3(f._key);
this.checksum = f.checksum();
this.byte_size = f.byteSize();
this.row_offset = row_offset;
this.rows = f.numRows();
this.num_columns = f.numCols();
this.row_count = row_count;
this.total_column_count = f.numCols();
this.column_offset = column_offset;
this.column_count = column_count;
this.columns = new ColV3[column_count];
Vec[] vecs = f.vecs();
Futures fs = new Futures();
// Compute rollups in parallel as needed, by starting all of them and using
// them when filling in the ColV3 Schemas
for( int i = 0; i < column_count; i++ )
vecs[column_offset + i].startRollupStats(fs);
for( int i = 0; i < column_count; i++ )
columns[i] = new ColV3(f._names[column_offset + i], vecs[column_offset + i], this.row_offset, this.row_count);
fs.blockForPending();
this.is_text = f.numCols()==1 && vecs[0] instanceof ByteVec;
this.default_percentiles = Vec.PERCENTILES;
ChunkSummary cs = FrameUtils.chunkSummary(f);
TwoDimTable chunk_summary_table = cs.toTwoDimTableChunkTypes();
this.chunk_summary = (TwoDimTableBase)Schema.schema(this.getSchemaVersion(), chunk_summary_table).fillFromImpl(chunk_summary_table);
TwoDimTable distribution_summary_table = cs.toTwoDimTableDistribution();
distribution_summary = (TwoDimTableBase)Schema.schema(this.getSchemaVersion(), distribution_summary_table).fillFromImpl(distribution_summary_table);
this._fr = f;
return this;
}
public void clearBinsField() {
for (ColV3 col: columns)
col.clearBinsField();
}
private abstract static class ColOp { abstract String op(ColV3 v); }
private String rollUpStr(ColV3 c, double d) {
return formatCell(c.domain!=null || "uuid".equals(c.type) || "string".equals(c.type) ? Double.NaN : d,null,c,4);
}
private String formatCell( double d, String str, ColV3 c, int precision ) {
if (Double.isNaN(d)) return "-";
if (c.domain != null) return c.domain[(int) d];
if ("uuid".equals(c.type) || "string".equals(c.type)) {
// UUID and String handling
if (str == null) return "-";
return "" + str + "";
} else {
Chunk chk = c._vec.chunkForRow(row_offset);
return PrettyPrint.number(chk, d, precision);
}
}
}
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