static Collection<String> fieldToAlias(Settings settings, Fields fields) {
FieldAlias fa = alias(settings);
List<String> names = asStrings(fields);
for (int i = 0; i < names.size(); i++) {
String original = names.get(i);
String alias = fa.toES(original);
if (alias != null) {
names.set(i, alias);
}
}
return names;
}
static Collection<String> columnToAlias(Settings settings) {
FieldAlias fa = alias(settings);
List<String> columnNames =
StringUtils.tokenize(settings.getProperty(HiveConstants.COLUMNS), ",");
// eliminate virtual columns
// we can't use virtual columns since some distro don't have this field...
// for (VirtualColumn vc : VirtualColumn.VIRTUAL_COLUMNS) {
// columnNames.remove(vc.getName());
// }
for (String vc : HiveConstants.VIRTUAL_COLUMNS) {
columnNames.remove(vc);
}
for (int i = 0; i < columnNames.size(); i++) {
String original = columnNames.get(i);
String alias = fa.toES(original);
if (alias != null) {
columnNames.set(i, alias);
}
}
return columnNames;
}
public boolean write(
Object object, ResourceFieldSchema field, Generator generator, boolean writeFieldName) {
byte type = (field != null ? field.getType() : DataType.findType(object));
if (writeFieldName) {
generator.writeFieldName(alias.toES(field.getName()));
}
if (object == null) {
generator.writeNull();
return true;
}
switch (type) {
case DataType.ERROR:
case DataType.UNKNOWN:
return handleUnknown(object, field, generator);
case DataType.NULL:
generator.writeNull();
break;
case DataType.BOOLEAN:
generator.writeBoolean((Boolean) object);
break;
case DataType.INTEGER:
generator.writeNumber(((Number) object).intValue());
break;
case DataType.LONG:
generator.writeNumber(((Number) object).longValue());
break;
case DataType.FLOAT:
generator.writeNumber(((Number) object).floatValue());
break;
case DataType.DOUBLE:
generator.writeNumber(((Number) object).doubleValue());
break;
case DataType.BYTE:
generator.writeNumber((Byte) object);
break;
case DataType.CHARARRAY:
generator.writeString(object.toString());
break;
case DataType.BYTEARRAY:
generator.writeBinary(((DataByteArray) object).get());
break;
// DateTime introduced in Pig 11
case 30: // DataType.DATETIME
generator.writeString(PigUtils.convertDateToES(object));
break;
// DateTime introduced in Pig 12
case 65: // DataType.BIGINTEGER
throw new SerializationException(
"Big integers are not supported by Elasticsearch - consider using a different type (such as string)");
// DateTime introduced in Pig 12
case 70: // DataType.BIGDECIMAL
throw new SerializationException(
"Big decimals are not supported by Elasticsearch - consider using a different type (such as string)");
case DataType.MAP:
ResourceSchema nestedSchema = field.getSchema();
// empty tuple shortcut
if (nestedSchema == null) {
generator.writeBeginObject();
generator.writeEndObject();
break;
}
ResourceFieldSchema[] nestedFields = nestedSchema.getFields();
generator.writeBeginObject();
// Pig maps are actually String -> Object association so we can save the key right away
for (Map.Entry<?, ?> entry : ((Map<?, ?>) object).entrySet()) {
generator.writeFieldName(alias.toES(entry.getKey().toString()));
write(entry.getValue(), nestedFields[0], generator, false);
}
generator.writeEndObject();
break;
case DataType.TUPLE:
nestedSchema = field.getSchema();
// empty tuple shortcut
if (nestedSchema == null) {
generator.writeBeginObject();
generator.writeEndObject();
break;
}
nestedFields = nestedSchema.getFields();
// use getAll instead of get(int) to avoid having to handle Exception...
List<Object> tuples = ((Tuple) object).getAll();
generator.writeBeginObject();
for (int i = 0; i < nestedFields.length; i++) {
String name = nestedFields[i].getName();
// handle schemas without names
name = (StringUtils.hasText(name) ? alias.toES(name) : Integer.toString(i));
generator.writeFieldName(name);
write(tuples.get(i), nestedFields[i], generator, false);
}
generator.writeEndObject();
break;
case DataType.BAG:
nestedSchema = field.getSchema();
// empty tuple shortcut
if (nestedSchema == null) {
generator.writeBeginArray();
generator.writeEndArray();
break;
}
ResourceFieldSchema bagType = nestedSchema.getFields()[0];
generator.writeBeginArray();
for (Tuple tuple : (DataBag) object) {
write(tuple, bagType, generator, false);
}
generator.writeEndArray();
break;
default:
if (writeUnknownTypes) {
return handleUnknown(object, field, generator);
}
return false;
}
return true;
}