Maxim Martynov created SPARK-44774:
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Summary: SaveMode.ErrorIfExists does not work with kafka-sql
Key: SPARK-44774
URL: https://issues.apache.org/jira/browse/SPARK-44774
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 3.4.1
Reporter: Maxim Martynov
I' trying to write batch dataframe to Kafka topic with {{mode="error"}}, but
when topic exists it does not raise exception - instead it appends data to a
topic.
Steps to reproduce:
1. Start Kafka:
docker-compose.yml
{code:yaml}
version: '3.9'
services:
zookeeper:
image: bitnami/zookeeper:3.8
environment:
ALLOW_ANONYMOUS_LOGIN: 'yes'
kafka:
image: bitnami/kafka:latest
restart: unless-stopped
ports:
- 9093:9093
environment:
ALLOW_PLAINTEXT_LISTENER: 'yes'
KAFKA_ENABLE_KRAFT: 'yes'
KAFKA_CLIENT_USERS: onetl
KAFKA_CLIENT_PASSWORDS: uufoFae9sahSoidoo0eagaidaoreif6z
KAFKA_CFG_ZOOKEEPER_CONNECT: zookeeper:2181
KAFKA_CFG_INTER_BROKER_LISTENER_NAME: INTERNAL_PLAINTEXT_ANONYMOUS
KAFKA_CFG_LISTENERS:
INTERNAL_PLAINTEXT_ANONYMOUS://:9092,EXTERNAL_PLAINTEXT_ANONYMOUS://:9093
KAFKA_CFG_ADVERTISED_LISTENERS:
INTERNAL_PLAINTEXT_ANONYMOUS://kafka:9092,EXTERNAL_PLAINTEXT_ANONYMOUS://localhost:9093
KAFKA_CFG_LISTENER_SECURITY_PROTOCOL_MAP:
INTERNAL_PLAINTEXT_ANONYMOUS:PLAINTEXT,EXTERNAL_PLAINTEXT_ANONYMOUS:PLAINTEXT
KAFKA_CFG_AUTO_CREATE_TOPICS_ENABLE: 'true'
depends_on:
- zookeeper
{code}
{code:bash}
docker-compose up -d
{code}
2. Start Spark session:
{code:bash}
pip install pyspark[sql]==3.4.1
{code}
{code:python}
from pyspark.sql import SparkSession
spark = SparkSession.builder.config("spark.jars.packages",
"org.apache.spark:spark-sql-kafka-0-10_2.12:3.4.1").getOrCreate()
{code}
3. Create DataFrame and write it to Kafka. First write using {{mode="append"}}
to create topic, then with {{mode="error"}} to raise because topic already
exist:
{code}
df = spark.createDataFrame([{"value": "string"}])
df.write.format("kafka").option("kafka.bootstrap.servers",
"localhost:9093").option("topic", "new_topic").mode("append").save()
# no exception is raised
df.write.format("kafka").option("kafka.bootstrap.servers",
"localhost:9093").option("topic", "new_topic").mode("error").save()
{code}
4. Check topic content - 2 rows are added to topic instead of one:
{code:python}
spark.read.format("kafka").option("kafka.bootstrap.servers",
"localhost:9093").option("subscribe", "new_topic").load().show(10, False)
{code}
{code}
+----+-------------------+---------+---------+------+-----------------------+-------------+
|key |value |topic |partition|offset|timestamp
|timestampType|
+----+-------------------+---------+---------+------+-----------------------+-------------+
|null|[73 74 72 69 6E 67]|new_topic|0 |0 |2023-08-11 09:39:35.813|0
|
|null|[73 74 72 69 6E 67]|new_topic|0 |1 |2023-08-11 09:39:36.122|0
|
+----+-------------------+---------+---------+------+-----------------------+-------------+
{code}
It looks like mode is checked by KafkaSourceProvider, but is not used at all:
https://github.com/apache/spark/blob/6b1ff22dde1ead51cbf370be6e48a802daae58b6/connector/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/KafkaSourceProvider.scala#L172-L178
So data is always appended to topic.
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