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https://issues.apache.org/jira/browse/AVRO-3408?focusedWorklogId=745045&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-745045
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ASF GitHub Bot logged work on AVRO-3408:
----------------------------------------
Author: ASF GitHub Bot
Created on: 21/Mar/22 13:21
Start Date: 21/Mar/22 13:21
Worklog Time Spent: 10m
Work Description: izemlyanskiy commented on pull request #1584:
URL: https://github.com/apache/avro/pull/1584#issuecomment-1073890523
I beg your very pardon for my ignorance, but @RyanSkraba and @rstata are 2
different people, right?
@RyanSkraba, thank you for your self-request, I look forward to your opinion
on this PR :pray:
@rstata you were the last person who touched
`org.apache.avro.io.parsing.ResolvingGrammarGenerator`. I've got a question for
you, in my PR we create a new instance of `GenericDatumReader` on every
conversion, it works fine but it's might be inefficient.
I thought to create such a reader in `ResolvingAction` or even create a new
`Action` and delegate all that conversation business to the action. But for
that, we need a reference of `org.apache.avro.generic.GenericData` here
`org.apache.avro.io.ResolvingDecoder#resolve`. I made an attempt and it could
be done with no harm to other code, but I didn't dare to offer such code
without a discussion.
Long story short, my suggestion is to add a `GenericData` parameter to
`org.apache.avro.io.DecoderFactory#resolvingDecoder`
and sink down it to `org.apache.avro.io.ResolvingDecoder` constructor,
method`org.apache.avro.io.ResolvingDecoder#resolve` and at the end make a field
in `org.apache.avro.io.parsing.ResolvingGrammarGenerator` in order to use it
in
`org.apache.avro.io.parsing.ResolvingGrammarGenerator#generate(org.apache.avro.Resolver.Action,
java.util.Map<java.lang.Object,org.apache.avro.io.parsing.Symbol>)` at this
moment:
```java
if (action instanceof Resolver.Promote) {
return Symbol.resolve(action.writer, action.reader,
simpleGen(action.writer, seen),
simpleGen(action.reader, seen));
```
(presumably in `Symbol.resolve` method)
Thank you for your time.
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Issue Time Tracking
-------------------
Worklog Id: (was: 745045)
Time Spent: 3h 20m (was: 3h 10m)
> 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
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.12.0
>
> Time Spent: 3h 20m
> Remaining Estimate: 0h
>
> 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}
> I'd love to read your opinion on all of that.
> Thank you in advance for your time, and sorry for the long issue description.
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