Ivan Zemlyanskiy created AVRO-3408: -------------------------------------- Summary: Schema evolution with logical types Key: AVRO-3408 URL: https://issues.apache.org/jira/browse/AVRO-3408 Project: Apache Avro Issue Type: Improvement Components: java Affects Versions: 1.11.0 Reporter: Ivan Zemlyanskiy
Hello! First of all, thank you for this project. I love Avro encoding from both technology and code culture points of view. (y) I know you recommend migrating schema by adding a new field and removing the old one in the future, but please-please-please consider my case as well. In my company, we have some DTOs, and it's about 200+ fields in total that we encode with Avro and send over the network. About a third of them have type `java.math.BigDecimal`. At some point, we discovered we send them with a schema like {code:json} { "name":"performancePrice", "type":{ "type":"string", "java-class":"java.math.BigDecimal" } } {code} That's a kind of disaster for us cos we have pretty much a high load with ~2 million RPS. So we start to think about migrating to something lighter than strings (no blame for choosing it as a default, I know BigDecimal has a lot of pitfalls, and string is the easiest way for encoding/decoding). It was fine to make a standard precision for all such fields, so we found `Conversions.DecimalConversion` and decided at the end of the day we were going to use this logical type with a recommended schema like {code:java} @Override public Schema getRecommendedSchema() { Schema schema = Schema.create(Schema.Type.BYTES); LogicalTypes.Decimal decimalType = LogicalTypes.decimal(MathContext.DECIMAL32.getPrecision(), DecimalUtils.MONEY_ROUNDING_SCALE); decimalType.addToSchema(schema); return schema; } {code} (we use `org.apache.avro.reflect.ReflectData`) It all looks good and promising, but the question is how to migrate to such schema? As I said, we have a lot of such fields, and migrating all of them with duplication fields with future removal might be painful and would cost us a considerable overhead. I made some tests and found out if two applications register the same `BigDecimalConversion` but for one application the `getRecommendedSchema()` is like the method above and for another application the `getRecommendedSchema()` is {code:java} @Override public Schema getRecommendedSchema() { Schema schema = Schema.create(Schema.Type.STRING); schema.addProp(SpecificData.CLASS_PROP, BigDecimal.class.getName()); return schema; } {code} so they can easily read each other messages using _SERVER_ schema. So, I made two applications and wired them up with `ProtocolRepository`, `ReflectResponder` and all that stuff, I found out it doesn't work. Because `org.apache.avro.io.ResolvingDecoder` totally ignores logical types for some reason. So as a result, one application specifically told "I encode this field as a byte array which supposed to be a logical type 'decimal' with precision N", but another application just tries to convert those bytes to a string and make a BigDecimal based on the result string. As a result, we got {code:java} java.lang.NumberFormatException: Character ' is neither a decimal digit number, decimal point, nor "e" notation exponential mark. {code} In my humble opinion, `org.apache.avro.io.ResolvingDecoder` should respect logical types in _SERVER_ (_ACTUAL_) schema and use a corresponding conversion instance for reading values. In my example, I'd say it might be {code} ResolvingDecoder#readString() -> read the actual logical type -> find BigDecimalConversion instance -> conversion.fromBytes(readValueWithActualSchema()) -> conversion.toCharSequence(readValueWithConversion) {code} Thank you in advance for your time, and sorry for the long post. -- This message was sent by Atlassian Jira (v8.20.1#820001)