wangbo commented on a change in pull request #4524:
URL: https://github.com/apache/incubator-doris/pull/4524#discussion_r484158638
##########
File path:
fe/spark-dpp/src/main/java/org/apache/doris/load/loadv2/dpp/SparkDpp.java
##########
@@ -358,12 +362,44 @@ private void processRollupTree(RollupTreeNode rootNode,
return Pair.of(keyMap.toArray(new Integer[keyMap.size()]),
valueMap.toArray(new Integer[valueMap.size()]));
}
- // repartition dataframe by partitionid_bucketid
- // so data in the same bucket will be consecutive.
- private JavaPairRDD<List<Object>, Object[]>
fillTupleWithPartitionColumn(SparkSession spark, Dataset<Row> dataframe,
+ /**
+ * check decimal,char/varchar
+ */
+ private boolean validateData(Object srcValue, EtlJobConfig.EtlColumn
etlColumn, ColumnParser columnParser,Row row) {
+
+ switch (etlColumn.columnType.toUpperCase()) {
+ case "DECIMALV2":
+ // TODO(wb): support decimal round; see be
DecimalV2Value::round
+ DecimalParser decimalParser = (DecimalParser) columnParser;
+ BigDecimal srcBigDecimal = (BigDecimal) srcValue;
+ if (srcValue != null &&
(decimalParser.getMaxValue().compareTo(srcBigDecimal) < 0 ||
decimalParser.getMinValue().compareTo(srcBigDecimal) > 0)) {
+ LOG.warn(String.format("decimal value is not valid for
defination, column=%s, value=%s,precision=%s,scale=%s",
+ etlColumn.columnName, srcValue.toString(),
srcBigDecimal.precision(), srcBigDecimal.scale()));
+ abnormalRowAcc.add(1);
+ return false;
+ }
+ break;
+ case "CHAR":
+ case "VARCHAR":
+ // TODO(wb) padding char type
+ if (srcValue != null && srcValue.toString().length() >
etlColumn.stringLength) {
+ LOG.warn(String.format("the length of input is too long
than schema. column_name:%s,input_str[%s],schema length:%s,actual length:%s",
+ etlColumn.columnName, row.toString(),
etlColumn.stringLength, srcValue.toString().length()));
+ return false;
+ }
+ break;
Review comment:
we just validate char/varchar and decimal here,so it't not necessary
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