Hello,
Issues :
* I and my team are trying to consume some kafka topics based on the
timestamps using startingOffsetsByTimestamps option, and the code works fine
when we run via a Databricks notebook.
* There is a need to setup the whole process in a local system (IntelliJ),
but the same code doesn’t work there. We are referring the official
documentation page, and using the exact same syntax and the same versions as
mentioned but somehow the code fails on the startingOffsetsByTimestamps line.
* The following versions are being used:
* Scala : 2.12.12
* Spark-sql : 3.0.1
* Spark-sql-kafka-0-10
* The code snippet is as follows, please suggest any changes or details
that we can use to fix this :
val spark =
SparkSession.builder().appName("Automation").master("local[*]").getOrCreate()
val df = spark
.read
.format("kafka")
.option("kafka.bootstrap.servers", bootstrap)
.option("subscribe", topic)
.option("kafka.security.protocol", "SSL")
.option("kafka.ssl.truststore.location", truststore_location)
.option("kafka.ssl.truststore.password", truststore_pwd)
.option("kafka.ssl.keystore.location", keystore_location)
.option("kafka.ssl.keystore.password", keystore_pwd)
.option("kafka.ssl.key.password", key_pwd)
.option("kafka.schema.registry.url", url)
.option("kafka.request.timeout.ms", "60000")
.option("kafka.session.timeout.ms", "60000")
.option("maxOffsetsPerTrigger", 3000000)
.option("failOnDataLoss", "false")
.option("dropMalformed", "true")
.option("startingOffsetsByTimestamp", """{"topic": {"0":
1000}}""")
.load()
df.show()
Error produced :
Exception in thread "main" java.lang.IllegalArgumentException: Expected e.g.
{"topicA": {"0": 123456789, "1": 123456789},
"topicB": {"0": 123456789, "1": 123456789}}
Expecations :
* I believe someone from kafka/spark team would help me resolve this issue,
so that I can proceed further with my work.
--
Thanks & Regards,
Yashasvini Rathore
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