leonardBang commented on a change in pull request #15658:
URL: https://github.com/apache/flink/pull/15658#discussion_r616374968
##########
File path:
flink-table/flink-table-common/src/main/java/org/apache/flink/table/utils/PrintUtils.java
##########
@@ -174,27 +215,238 @@ public static void printAsTableauForm(
printWriter.flush();
}
- public static String[] rowToString(Row row) {
- return rowToString(row, NULL_COLUMN, false);
+ public static String[] rowToString(
+ Row row, ResolvedSchema resolvedSchema, ZoneId sessionTimeZone) {
+ return rowToString(row, NULL_COLUMN, false, resolvedSchema,
sessionTimeZone);
}
- public static String[] rowToString(Row row, String nullColumn, boolean
printRowKind) {
+ public static String[] rowToString(
+ Row row,
+ String nullColumn,
+ boolean printRowKind,
+ ResolvedSchema resolvedSchema,
+ ZoneId sessionTimeZone) {
final int len = printRowKind ? row.getArity() + 1 : row.getArity();
final List<String> fields = new ArrayList<>(len);
if (printRowKind) {
fields.add(row.getKind().shortString());
}
for (int i = 0; i < row.getArity(); i++) {
final Object field = row.getField(i);
+ final LogicalType fieldType =
+
resolvedSchema.getColumnDataTypes().get(i).getLogicalType();
if (field == null) {
fields.add(nullColumn);
} else {
- fields.add(StringUtils.arrayAwareToString(field));
+ fields.add(
+ StringUtils.arrayAwareToString(
+ normalizeTimestamp(field, fieldType,
sessionTimeZone)));
}
}
return fields.toArray(new String[0]);
}
+ /**
+ * Normalizes field that contains TIMESTAMP and TIMESTAMP_LTZ type data.
+ *
+ * <p>This method supports array type and nested type.
+ */
+ private static Object normalizeTimestamp(
Review comment:
After discussion with Jark, we think we can refactor this in the future
by adding a string representation for all internal data structure (i.e.
RowData), in this way we can reuse the string representation for output and
planner codegen
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