Spark schema <-> odcs conversion - #1
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| DataType dataType = field.dataType(); | ||
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| // Map via metadata / type | ||
| if (dataType instanceof MapType mapType |
| String trimmed = physicalType.trim(); | ||
| Matcher m = DECIMAL.matcher(trimmed); | ||
| if (m.matches()) { | ||
| return Optional.of(new DecimalSpec(Integer.parseInt(m.group(1)), Integer.parseInt(m.group(2)))); |
| String trimmed = physicalType.trim(); | ||
| Matcher m = DECIMAL.matcher(trimmed); | ||
| if (m.matches()) { | ||
| return Optional.of(new DecimalSpec(Integer.parseInt(m.group(1)), Integer.parseInt(m.group(2)))); |
| } | ||
| Matcher m = VARCHAR.matcher(physicalType.trim()); | ||
| if (m.matches()) { | ||
| return Optional.of(Integer.parseInt(m.group(1))); |
| return parent + "." + name; | ||
| } | ||
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| private void failOrWarn(String path, String message, DataType fallback) { |
| private OdcsMetadata() { | ||
| } | ||
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| public static Metadata build(SchemaProperty property, String sparkFieldName, boolean usedPhysicalName) { |
| report.warn(path, message + "; falling back to " + fallback.simpleString()); | ||
| } | ||
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| private void failOrWarn(String path, String message, StructType fallback) { |
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