MySQL / MSSQL : numeric.mapping doesn't work for DECIMAL fields

[rmoff]

I can't get numeric.mapping to work with MySQL and Confluent Platform 5.1. Steps to reproduce below.

Create MySQL table:

use demo;

create table transactions (
	txn_id INT,
	customer_id INT,
	amount DECIMAL(5,2),
	currency VARCHAR(50),
	txn_timestamp VARCHAR(50)
);

insert into transactions (txn_id, customer_id, amount, currency, txn_timestamp) values (3, 2, 17.13, 'EUR', '2018-04-30T21:30:39Z');

Inspect table:

mysql> describe transactions;
+---------------+--------------+------+-----+---------+-------+
| Field         | Type         | Null | Key | Default | Extra |
+---------------+--------------+------+-----+---------+-------+
| txn_id        | int(11)      | YES  |     | NULL    |       |
| customer_id   | int(11)      | YES  |     | NULL    |       |
| amount        | decimal(5,2) | YES  |     | NULL    |       |
| currency      | varchar(50)  | YES  |     | NULL    |       |
| txn_timestamp | varchar(50)  | YES  |     | NULL    |       |
+---------------+--------------+------+-----+---------+-------+
5 rows in set (0.00 sec)

Create connector

curl -X POST http://localhost:8083/connectors -H "Content-Type: application/json" -d '{
          "name": "jdbc_source_mysql_12a",
          "config": {
                  "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector",
                  "connection.url": "jdbc:mysql://mysql:3306/demo",
                  "connection.user": "connect_user",
                  "connection.password": "asgard",
                  "topic.prefix": "mysql-12a-",
                  "numeric.mapping": "best_fit",
                  "table.whitelist" : "demo.transactions",
                  "mode":"bulk",
                  "poll.interval.ms" : 3600000
                  }
          }'

Even though "numeric.mapping": "best_fit", Kafka Connect stores the DECIMAL(5,2) as a Decimal, serialised to bytes in Avro:

$ curl -s "http://localhost:8081/subjects/mysql-12a-transactions-value/versions/1"|jq '.schema|fromjson.fields[] | select (.name == "amount")'
{
  "name": "amount",
  "type": [
    "null",
    {
      "type": "bytes",
      "scale": 2,
      "precision": 64,
      "connect.version": 1,
      "connect.parameters": {
        "scale": "2"
      },
      "connect.name": "org.apache.kafka.connect.data.Decimal",
      "logicalType": "decimal"
    }
  ],
  "default": null
}

Connect Worker log excerpt:

INFO Kafka version : 2.1.0-cp1 (org.apache.kafka.common.utils.AppInfoParser)
…
INFO JdbcSourceTaskConfig values:
 batch.max.rows = 100
 catalog.pattern = null
 connection.attempts = 3
 connection.backoff.ms = 10000
 connection.password = [hidden]
 connection.url = jdbc:mysql://mysql:3306/demo
 connection.user = connect_user
 dialect.name =
 incrementing.column.name =
 mode = bulk
 numeric.mapping = best_fit
 numeric.precision.mapping = false
 poll.interval.ms = 3600000
 query =
 schema.pattern = null
 table.blacklist = []
 table.poll.interval.ms = 60000
 table.types = [TABLE]
 table.whitelist = [demo.transactions]
 tables = [`demo`.`transactions`]
 timestamp.column.name = []
 timestamp.delay.interval.ms = 0
 topic.prefix = mysql-12a-
 validate.non.null = true
 (io.confluent.connect.jdbc.source.JdbcSourceTaskConfig)
…
DEBUG Checking for next block of results from BulkTableQuerier{table='"demo"."transactions"', query='null', topicPrefix='mysql-12a-'} (io.confluent.connect.jdbc.source.JdbcSourceTask)
DEBUG BulkTableQuerier{table='"demo"."transactions"', query='null', topicPrefix='mysql-12a-'} prepared SQL query: SELECT * FROM `demo`.`transactions` (io.confluent.connect.jdbc.source.BulkTableQuerier)
DEBUG DECIMAL with precision: '5' and scale: '2' (io.confluent.connect.jdbc.dialect.MySqlDatabaseDialect)
DEBUG DECIMAL with precision: '5' and scale: '2' (io.confluent.connect.jdbc.dialect.MySqlDatabaseDialect)
DEBUG Returning 100 records for BulkTableQuerier{table='"demo"."transactions"', query='null', topicPrefix='mysql-12a-'} (io.confluent.connect.jdbc.source.JdbcSourceTask)
…
kafka-connect_1_8eb73e80dda1 | [2019-01-07 13:37:50,920] DEBUG Sending POST with input {"schema":"{\"type\":\"record\",\"name\":\"transactions\",\"fields\":[{\"name\":\"txn_id\",\"type\":[\"null\",\"int\"],\"default\":null},{\"name\":\"customer_id\",\"type\":[\"null\",\"int\"],\"default\":null},{\"name\":\"amount\",\"type\":[\"null\",{\"type\":\"bytes\",\"scale\":2,\"precision\":64,\"connect.version\":1,\"connect.parameters\":{\"scale\":\"2\"},\"connect.name\":\"org.apache.kafka.connect.data.Decimal\",\"logicalType\":\"decimal\"}],\"default\":null},{\"name\":\"currency\",\"type\":[\"null\",\"string\"],\"default\":null},{\"name\":\"txn_timestamp\",\"type\":[\"null\",\"string\"],\"default\":null}],\"connect.name\":\"transactions\"}"} to http://schema-registry:8081/subjects/mysql-12a-transactions-value/versions (io.confluent.kafka.schemaregistry.client.rest.RestService)

I've tried this with three different settings, each still results in the amount field serialised to bytes in Avro:

• "numeric.mapping": "best_fit"
• "numeric.mapping": "precision_only"
• "numeric.precision.mapping": true

Per docs I am expecting to see the decimal(5,2) serialised to Avro FLOAT64(I think - but at least, not bytes)

[rmoff]

does numeric.mapping only apply to NUMERIC types, not DECIMAL?

kafka-connect-jdbc/src/main/java/io/confluent/connect/jdbc/dialect/GenericDatabaseDialect.java

Lines 1146 to 1189 in b23e312

	case Types.NUMERIC:
	if (mapNumerics == NumericMapping.PRECISION_ONLY) {
	int precision = defn.precision();
	int scale = defn.scale();
	log.trace("NUMERIC with precision: '{}' and scale: '{}'", precision, scale);
	if (scale == 0 && precision < 19) { // integer
	if (precision > 9) {
	return rs -> rs.getLong(col);
	} else if (precision > 4) {
	return rs -> rs.getInt(col);
	} else if (precision > 2) {
	return rs -> rs.getShort(col);
	} else {
	return rs -> rs.getByte(col);
	}
	}
	} else if (mapNumerics == NumericMapping.BEST_FIT) {
	int precision = defn.precision();
	int scale = defn.scale();
	log.trace("NUMERIC with precision: '{}' and scale: '{}'", precision, scale);
	if (precision < 19) { // fits in primitive data types.
	if (scale < 1 && scale >= NUMERIC_TYPE_SCALE_LOW) { // integer
	if (precision > 9) {
	return rs -> rs.getLong(col);
	} else if (precision > 4) {
	return rs -> rs.getInt(col);
	} else if (precision > 2) {
	return rs -> rs.getShort(col);
	} else {
	return rs -> rs.getByte(col);
	}
	} else if (scale > 0) { // floating point - use double in all cases
	return rs -> rs.getDouble(col);
	}
	}
	}
	// fallthrough
	case Types.DECIMAL: {
	final int precision = defn.precision();
	log.debug("DECIMAL with precision: '{}' and scale: '{}'", precision, defn.scale());
	final int scale = decimalScale(defn);
	return rs -> rs.getBigDecimal(col, scale);
	}

[rmoff]

https://dev.mysql.com/doc/refman/8.0/en/fixed-point-types.html

In MySQL, NUMERIC is implemented as DECIMAL

So the following DDL:

CREATE TABLE NUM_TEST (
	TXN_ID INT,
	CUSTOMER_ID INT,
	AMOUNT_01 DECIMAL(5,2),
	AMOUNT_02 NUMERIC(5,2), 
	AMOUNT_03 DECIMAL(5),
	AMOUNT_04 DECIMAL
);

Creates a table like this - note that AMOUNT_02 whilst declared as NUMERIC is created as a DECIMAL:

mysql> DESCRIBE NUM_TEST;
+-------------+---------------+------+-----+---------+-------+
| Field       | Type          | Null | Key | Default | Extra |
+-------------+---------------+------+-----+---------+-------+
| TXN_ID      | int(11)       | YES  |     | NULL    |       |
| CUSTOMER_ID | int(11)       | YES  |     | NULL    |       |
| AMOUNT_01   | decimal(5,2)  | YES  |     | NULL    |       |
| AMOUNT_02   | decimal(5,2)  | YES  |     | NULL    |       |
| AMOUNT_03   | decimal(5,0)  | YES  |     | NULL    |       |
| AMOUNT_04   | decimal(10,0) | YES  |     | NULL    |       |
+-------------+---------------+------+-----+---------+-------+
6 rows in set (0.01 sec)

(MySQL Server version: 8.0.13)

[rmoff]

Contrast to Postgres:

CREATE TABLE NUM_TEST (
	TXN_ID INT,
	CUSTOMER_ID INT,
	AMOUNT_01 DECIMAL(5,2),
	AMOUNT_02 NUMERIC(5,2), 
	AMOUNT_03 DECIMAL(5),
	AMOUNT_04 DECIMAL
);

All columns are stored as NUMERIC:

demo=# \d num_test
                   Table "public.num_test"
   Column    |     Type     | Collation | Nullable | Default
-------------+--------------+-----------+----------+---------
 txn_id      | integer      |           |          |
 customer_id | integer      |           |          |
 amount_01   | numeric(5,2) |           |          |
 amount_02   | numeric(5,2) |           |          |
 amount_03   | numeric(5,0) |           |          |
 amount_04   | numeric      |           |          |

	col1	col2	col3	col4
Postgres column definition	DECIMAL(5,2)	NUMERIC(5,2)	DECIMAL(5)	DECIMAL
Source data in Postgres	100.01	100.02	100	100
numeric.mapping = none (same as leaving it unset)	Bytes '\u0011	Bytes Øî	Bytes d	Bytes d
numeric.mapping = best_fit	Double 100.01	Double 100.02	Int 100	Int 100
numeric.mapping = precision_only	Bytes '\u0011	Bytes Øî	Int 100	Int 100

(Postgres 11.1)

Postgres notes: https://gist.github.com/rmoff/7bb46a0b6d27982a5fb7a103bb7c95b9

[rmoff]

MS SQL notes : https://gist.github.com/rmoff/7bb46a0b6d27982a5fb7a103bb7c95b9#testing-numericmapping-in-ms-sql-server-2017

	col1	col2	col3	col4
MSSQL column definition	DECIMAL(5,2)	NUMERIC(5,2)	DECIMAL(5)	DECIMAL
MSSQL created column	decimal length 5 precision 5 scale 2	numeric length 5 precision 5 scale 2	decimal length 5 precision 5 scale 0	decimal length 9 precision 18 scale 0
Source data in MSSQL	100.01	100.02	100	100
numeric.mapping = none (same as leaving it unset)	Bytes '\u0011	Bytes Øî	Bytes d	Bytes d
numeric.mapping = best_fit	Bytes '\u0011	Double 100.02	Bytes d	Bytes d
numeric.mapping = best_fit (query used to CAST all DECIMAL fields to NUMERIC)	Double 100.01	Double 100.02	Int 100	Int 100
numeric.mapping = precision_only	Bytes '\u0011	Bytes Øî	Int 100	Int 100

The same problem exists with DECIMAL fields being ignored. Since MS SQL accepts both DECIMAL and NUMERIC as native data types, use NUMERIC for Kafka Connect to correctly ingest the values when using numeric.precision=best_fit. If changing the source schema isn't an option then you can use query mode, demonstrated here.

[anssip]

I am facing a problem with MySql and decimal data types. The values end up as corrupt strings in the Kafka topic. Without using schemas the values look like this when listing with console-consumer:

"revenue":"AfQ="

I tried if registering an Avro schema would help. I made the type of this revenue field to be float in the schema and created a JDBC source connector to fill the topic. But this connector fails with following

org.apache.kafka.common.errors.SerializationException: Error registering Avro schema: 
...
{\"name\":\"revenue\",\"type\":{\"type\":\"bytes\",\"scale\":2,\"precision\":64,\"connect.version\":1,\"connect.parameters\":{\"scale\":\"2\"},\"connect.name\":\"org.apache.kafka.connect.data.Decimal\",\"logicalType\":\"decimal\"}}
...

Seems like it tries to register a new schema that is incompatible with my previously created schema. It tries to use type bytes for this revenue field (and for other decimal fields).

My table in MySQL looks like this:

mysql> describe v_game_transaction;
+-------------------+---------------+------+-----+---------------------+-------+
| Field             | Type          | Null | Key | Default             | Extra |
+-------------------+---------------+------+-----+---------------------+-------+
| id                | bigint(20)    | NO   |     | 0                   |       |
| revenue           | decimal(10,2) | NO   |     | NULL                |       |
...

Is there some way to work around this issue now?

[rmoff]

DECIMAL isn't supported for numeric.mapping. There isn't a way to work around this that I'm aware of. The data isn't "corrupt", it's just a BigDecimal.

For more details see https://www.confluent.io/blog/kafka-connect-deep-dive-jdbc-source-connector#bytes-decimals-numerics

[anssip]

I tried to work around this issue by using a SMT cast. I changed the type of the column to varchar in the DB view i'm using here, and then casting it with

      "transforms": "Cast",
      "transforms.Cast.type": "org.apache.kafka.connect.transforms.Cast$Value",
      "transforms.Cast.spec": "revenue:float64"

But now the connector fails with: [{"state":"FAILED","trace":"org.apache.kafka.connect.errors.DataException: Invalid Java object for schema type INT64: class java.sql.Timestamp for field: \"started\

Adding this cast transform causes it to fail with datetime fields! Found this issue relating to cast transforms

My second attempt was to fix the the connector code:

kafka-connect-jdbc/src/main/java/io/confluent/connect/jdbc/dialect/GenericDatabaseDialect.java

Line 1146 in b23e312

case Types.NUMERIC:

I changed that line to include both DECIMAL and NUMERIC

      case Types.DECIMAL:
      case Types.NUMERIC: {
        if (mapNumerics == NumericMapping.PRECISION_ONLY) {
.....

Using this hacked-up connector it produces a bit different kind of bytes data in the topic. But seems like that is not the correct way to fix the issue :-)

[aliasbadwolf]

@anssip Here is a small code snippet that can help you in getting the data back in correct form (written in scala; you can change it to Java if you want). Essentially, it is not corrupt data it is just base64 encoded string of "unscaled" value of BigDecimal. Kafka Connect converts NUMERIC type having precision and scale to BigDecimal internally (and timestamps to long/epoch) when using AVRO (since its essentially a JSON.

As you already have schema available with you just get the precision and scale from there and pass it along while recreating a BigDecimal back and once you have the final BigDecimal you can get longValue or intValue or doubleValue from it.

Hope it helps !

//a bigdecimal with precision 4 and scale 3
    val bd = new BigDecimal("1.234")
    println(bd)
    println(bd.precision()) //prints 4
    println(bd.scale) //prints 3
    val encoded = Base64.getEncoder.encodeToString(bd.unscaledValue().toByteArray())
    println(encoded) // prints "BNI="
    
    val decoded = Base64.getDecoder.decode(encoded)
    val bi = new BigInteger(decoded)
    println(bi) //prints 1234
    val bd2 = new BigDecimal(bi, bd.scale)
    println(bd2) //prints 1.234

[anssip]

Thanks, @aliasbadwolf for that tip. I am actually able to convert it to a valid number. I am now doing it with JavaScript as I'm doing the stream processing in Node.js

But my goal here was to streamline my data pipeline and not use any stream processing at all. I'd like to stream the data directly to Elasticsearch without doing any processing (and number conversion). Just one JDBC source connector pushing the data into a topic and from there one sink to push it to Elasticsearch.

[kinghuang]

Is there anything being done about this issue? I'm working with a large existing Oracle database, where the primary keys are all declared as NUMBER (no precision/scale). As documented by @rmoff in https://gist.github.com/rmoff/7bb46a0b6d27982a5fb7a103bb7c95b9#file-oracle-md, these end up as bytes no matter what numeric.mapping is set to.

While specifying a custom query is a workaround, it's an absolute pain since there are a few hundred tables. SMTs do seem to work in limited testing.

[syedabdulkather]

Hi Guys,

Is there any workaround on the above issues

[murx66]

Hi there guys!

I'm actualli working with a JDBC connector between Oracle and KafkaConnect.
I have some NUMBER(38,0) fields in my database table.
I'm actually having the same error:

• java.lang.IllegalArgumentException: Invalid decimal scale: 127 (greater than precision: 64)

It's some fix for this or a good workaround?
Or it's pushpavanthar PR (#725) adding and working in the last versions?

Thanks a lot!

[vishnu2497]

Hi guys

Is there any update on this issue?

Is any way to take decimal type values from MySQL using JDBC source connector!!

#725

in the above he said like that is solved and will fix this issue,is this fixed!!!

[kbegrow]

Hi,
I have the same question regarding MySQL and it seems not fixed yet.
I think the PR by pushpavanthar is not merged yet. :-(

[h-vetinari]

I'm working with a large existing Oracle database, where the primary keys are all declared as NUMBER (no precision/scale). As documented by @rmoff in https://gist.github.com/rmoff/7bb46a0b6d27982a5fb7a103bb7c95b9#file-oracle-md, these end up as bytes no matter what numeric.mapping is set to.

Mid-2022: NUMBER with missing precision scale will not be transformed, even using best_fit_eager_double.

As mentioned by @kinghuang, SMTs work in limited fashion, e.g.

transforms.AdjustPrecision.type=com.github.jcustenborder.kafka.connect.transform.common.AdjustPrecisionAndScale$Value
transforms.AdjustPrecision.precision.value=38
transforms.AdjustPrecision.scale.value=10
transforms.AdjustPrecision.precision.mode=undefined
transforms.AdjustPrecision.scale.mode=undefined

but even then this seems to get applied in parallel or after numeric.mapping, and so the resulting schema still ends up with decimal types!

I think that especially best_fit_eager_double should also apply if scale/precision are missing.

[monicaandhare]

numeric.mapping best_fit_eager_double works for numeric(20,2) (without precision it doesn't work) but till 7 digits eg. 1234567.11 but beyond this 12345678.11 will store something like this 1.234567811E7

[ordiy]

use Cast SMT can solved this bug.

        "transforms":"castDecimalToDouble",
         "transforms.castDecimalToDouble.type": "org.apache.kafka.connect.transforms.Cast$Value",
         "transforms.castDecimalToDouble.spec": "app_score:float32"  # or float64

result

"app_score":4.5 # before  "app_score":"AcI="