Comments (3)
Hello, I am not sure if this is problem with Abris, since it's Kafka exception. Could you post the whole Exception?
If you try yo read from Kafka and just show
the raw data without calling Abris is it working fine?
from abris.
@cerveada Thanks for going through it.
Exception: Caused by: java.lang.ClassCastException: org.apache.spark.sql.catalyst.expressions.GenericRow cannot be cast to org.apache.avro.generic.GenericRecord
I do get byte array by doing: I was looking for a way by which I can skip schema validation and just print the incoming message(not as byte array)
kafkaDataFrame .writeStream .format("console") .option("truncate", "false") .start() .awaitTermination()
Batch: 1
|[00 00 00 01 33 BA 01]|[00 00 00 01 90 02 BA 01 48 39 39 61 35 64 31 37 32 2D 31 32 38 65 2D 34 65 37 39 2D 39 34 65 61 2D 38 65 30 63 64 30 62 31 37 36 36 32 48 61 32 35 62 35 37 66 66 2D 62 33 61 38 2D 34 64 64 32 2D 39 63 36 37 2D 65 32 37 37 31 35 62 32 39 33 34 63 02 40 30 63 61 36 64 35 35 37 39 30 36 63 34 30 66 30 33 63 30 38 39 32 39 65 35 34 36 66 37 66 37 61 00 12 63 61 73 74 6C 69 67 68 74 32 54 65 61 6D 20 4C 65 61 64 65 72 62 6F 61 72 64 20 50 72 6F 67 72 61 6D 73 02 50 54 68 69 73 20 69 73 20 61 20 63 6F 6D 70 65 74 69 74 69 76 65 20 77 61 6C 6B 69 6E 67 20 63 68 61 6C 6C 65 6E 67 65 2E CC 99 02 F0 99 02 CC 99 02 F0 99 02 0C 2D 30 37 3A 30 30 16 4C 45 41 44 45 52 42 4F 41 52 44 00 00 00 02 34 02 92 08 7B 22 6D 61 78 69 6D 75 6D 53 69 7A 65 22 3A 33 2C 22 6A 6F 69 6E 53 74 72 61 74 65 67 79 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 4F 72 41 75 74 6F 22 2C 22 61 75 74 6F 4A 6F 69 6E 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 41 75 74 6F 22 2C 22 63 72 65 61 74 65 54 65 61 6D 49 66 4E 6F 74 45 78 69 73 74 73 22 3A 74 72 75 65 2C 22 74 65 61 6D 41 6C 6C 6F 63 61 74 69 6F 6E 41 6C 67 6F 72 69 74 68 6D 22 3A 22 53 45 51 55 45 4E 54 49 41 4C 22 7D 2C 22 75 73 65 72 53 65 6C 65 63 74 65 64 4A 6F 69 6E 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 22 7D 7D 2C 22 63 72 65 61 74 65 53 74 72 61 74 65 67 79 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 4F 72 41 75 74 6F 22 2C 22 76 69 73 69 62 69 6C 69 74 69 65 73 22 3A 5B 22 50 55 42 4C 49 43 22 2C 22 50 52 49 56 41 54 45 22 5D 2C 22 61 75 74 6F 43 72 65 61 74 65 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 41 75 74 6F 22 2C 22 76 69 73 69 62 69 6C 69 74 69 65 73 22 3A 5B 22 50 55 42 4C 49 43 22 5D 2C 22 74 65 61 6D 4E 61 6D 65 50 72 6F 76 69 64 65 72 22 3A 22 52 41 4E 44 4F 4D 5F 4C 49 4E 45 22 7D 2C 22 75 73 65 72 53 70 65 63 69 66 69 65 64 43 72 65 61 74 65 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 22 2C 22 76 69 73 69 62 69 6C 69 74 69 65 73 22 3A 5B 22 50 55 42 4C 49 43 22 2C 22 50 52 49 56 41 54 45 22 5D 7D 7D 7D 02 70 7B 22 70 72 6F 67 72 61 6D 49 6E 73 74 61 6E 63 65 49 64 22 3A 22 37 31 66 65 66 35 34 32 37 39 32 38 34 30 31 61 62 35 61 38 38 63 63 66 61 39 37 66 38 62 63 65 22 7D 00 28 32 30 31 39 2D 30 35 2D 30 36 54 31 39 3A 30 35 3A 30 34 5A 28 32 30 31 39 2D 31 32 2D 31 37 54 30 37 3A 32 31 3A 34 33 5A 02 48 64 64 33 66 61 32 35 66 2D 61 34 32 66 2D 34 65 61 34 2D 38 34 33 65 2D 31 62 39 64 37 63 33 38 39 31 62 64 02 BA 01 48 39 39 61 35 64 31 37 32 2D 31 32 38 65 2D 34 65 37 39 2D 39 34 65 61 2D 38 65 30 63 64 30 62 31 37 36 36 32 48 61 32 35 62 35 37 66 66 2D 62 33 61 38 2D 34 64 64 32 2D 39 63 36 37 2D 65 32 37 37 31 35 62 32 39 33 34 63 02 40 30 63 61 36 64 35 35 37 39 30 36 63 34 30 66 30 33 63 30 38 39 32 39 65 35 34 36 66 37 66 37 61 00 12 63 61 73 74 6C 69 67 68 74 32 54 65 61 6D 20 4C 65 61 64 65 72 62 6F 61 72 64 20 50 72 6F 67 72 61 6D 73 02 52 54 68 69 73 20 69 73 20 61 20 63 6F 6D 70 65 74 69 74 69 76 65 20 77 61 6C 6B 69 6E 67 20 63 68 61 6C 6C 65 6E 67 65 2E 31 CC 99 02 F0 99 02 CC 99 02 F0 99 02 0C 2D 30 37 3A 30 30 16 4C 45 41 44 45 52 42 4F 41 52 44 00 00 00 02 34 02 92 08 7B 22 6D 61 78 69 6D 75 6D 53 69 7A 65 22 3A 33 2C 22 6A 6F 69 6E 53 74 72 61 74 65 67 79 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 4F 72 41 75 74 6F 22 2C 22 61 75 74 6F 4A 6F 69 6E 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 41 75 74 6F 22 2C 22 63 72 65 61 74 65 54 65 61 6D 49 66 4E 6F 74 45 78 69 73 74 73 22 3A 74 72 75 65 2C 22 74 65 61 6D 41 6C 6C 6F 63 61 74 69 6F 6E 41 6C 67 6F 72 69 74 68 6D 22 3A 22 53 45 51 55 45 4E 54 49 41 4C 22 7D 2C 22 75 73 65 72 53 65 6C 65 63 74 65 64 4A 6F 69 6E 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 22 7D 7D 2C 22 63 72 65 61 74 65 53 74 72 61 74 65 67 79 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 4F 72 41 75 74 6F 22 2C 22 76 69 73 69 62 69 6C 69 74 69 65 73 22 3A 5B 22 50 55 42 4C 49 43 22 2C 22 50 52 49 56 41 54 45 22 5D 2C 22 61 75 74 6F 43 72 65 61 74 65 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 41 75 74 6F 22 2C 22 76 69 73 69 62 69 6C 69 74 69 65 73 22 3A 5B 22 50 55 42 4C 49 43 22 5D 2C 22 74 65 61 6D 4E 61 6D 65 50 72 6F 76 69 64 65 72 22 3A 22 52 41 4E 44 4F 4D 5F 4C 49 4E 45 22 7D 2C 22 75 73 65 72 53 70 65 63 69 66 69 65 64 43 72 65 61 74 65 54 65 61 6D 53 74 72 61 74 65 67 79 43 6F 6E 66 69 67 75 72 61 74 69 6F 6E 22 3A 7B 22 74 79 70 65 22 3A 22 55 73 65 72 22 2C 22 76 69 73 69 62 69 6C 69 74 69 65 73 22 3A 5B 22 50 55 42 4C 49 43 22 2C 22 50 52 49 56 41 54 45 22 5D 7D 7D 7D 02 70 7B 22 70 72 6F 67 72 61 6D 49 6E 73 74 61 6E 63 65 49 64 22 3A 22 37 31 66 65 66 35 34 32 37 39 32 38 34 30 31 61 62 35 61 38 38 63 63 66 61 39 37 66 38 62 63 65 22 7D 00 28 32 30 31 39 2D 30 35 2D 30 36 54 31 39 3A 30 35 3A 30 34 5A 28 32 30 31 39 2D 31 32 2D 31 37 54 31 35 3A 31 38 3A 30 36 5A 02 48 64 64 33 66 61 32 35 66 2D 61 34 32 66 2D 34 65 61 34 2D 38 34 33 65 2D 31 62 39 64 37 63 33 38 39 31 62 64 02 16 30 2E 38 2E 33 2E 46 69 6E 61 6C 1A 64 65 6E 2D 71 61 30 31 2D 64 62 31 31 FE FF FF FF 1F DC C6 C7 DF 0B 00 20 6D 79 73 71 6C 2D 62 69 6E 2E 30 30 30 30 33 31 BA E4 B8 43 00 00 00 02 F8 FF 94 01 02 26 63 68 61 6C 6C 65 6E 67 65 73 32 5F 64 65 6E 71 61 30 31 02 14 63 68 61 6C 6C 65 6E 67 65 73 00 02 75 02 C6 C0 80 C7 E2 5B]|topic-name|0 |5212 |2019-12-17 07:18:06.412|0 |
from abris.
I'm not sure what exactly do you mean by validation. If the schema is not valid how do you want to deserialize the data? I would expect invalid schema to cause errors during deserialization.
When you use from_confluent_avro
Abris work with two schemas. Reader schema loaded from schema registry according to configuration and writer schema also loaded froms chema registry, but this time by schema id that is on start of the payload (According to confluent specs). This two schemas must be compatible and there is no way to turn this off.
The other option is to use from_avro
and provide the schema by yourself. This way you can specify any schema you want, but if there is this schema_id on start of the payload you need to trim it by yourself before handing the column to Abris.
from abris.
Related Issues (20)
- from_avro converts `\uFFFD` to a question mark HOT 1
- schema registry being called with http instead of https HOT 2
- Improve code-coverage & add GH check action HOT 1
- Fix JaCoCo CI for PRs from forked repos HOT 1
- update madrapps/jacoco-report
- Detect different schema versions in batch HOT 5
- Revert pull_request action back HOT 3
- TopicNameStrategy issue HOT 1
- Split GitHub actions for tests and test coverage
- Multiple schemas in one topic example HOT 1
- Spark 3.4 Support HOT 13
- malformed records to topic HOT 2
- foreach batch download by schem id HOT 3
- Container exited with a non-zero exit code 137 | Out of memory HOT 5
- Issues running inside Scala notebook on databricks HOT 1
- Fix tests for Spark 3.5.0
- Fix NoSuchMethodException in Spark 3.5.x
- get key from avro message HOT 3
- Compatibility with Spark 3.5 HOT 3
- Version 6.4.0 failing for Spark 3.5.0 HOT 2
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from abris.