How to include both "latest" and "JSON with specific Offset" in "startingOffsets" while importing data from Kafka into Spark Structured Streaming - apache-spark

Question

I have a streaming query saving data into filesink. I am using .option("startingOffsets", "latest") and a checkpoint location. If there is any down time on Spark and when the streaming query starts again i do not want to start processing where the query left off when it went down rather than this scenario i would also like to add ("startingOffsets", """ {"topicA":{"0":23,"1":-1},"topicB":{"0":-2}} """) by specifying the user defined offset which needs to process from.
i tried doing this with different programs but i need to achieve this in one single program
import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions._
import org.apache.spark.sql.streaming.Trigger
object OSB_offset_kafkaToSpark {
def main(args: Array[String]): Unit = {
val spark = SparkSession.
builder().
appName("OSB_kafkaToSpark").
config("spark.mongodb.output.uri", "spark.mongodb.output.uri=mongodb://somemongodb.com:27018").
getOrCreate()
println("SparkSession -> "+spark)
import spark.implicits._
val df = spark
.readStream
.format("kafka")
.option("kafka.bootstrap.servers", "somekafkabroker:9092, somekafkabroker:9092")
.option("subscribe", "someTopic")
.option("startingOffsets", "latest")
.option("startingOffsets",""" {"someTopic":{"0":438521}}, "someTopic":{"1":438705}}, "someTopic":{"2":254180}}""")
.option("endingOffsets",""" {"someTopic":{"0":-1}}, "someTopic":{"1":-1}}, "someTopic":{"2":-1}} """)
.option("failOnDataLoss", "false")
.load()
val dfs = df.selectExpr("CAST(value AS STRING)")
val data = dfs.withColumn("splitted", split($"value", "/"))
.select($"splitted".getItem(4).alias("region"), $"splitted".getItem(5).alias("service"), col("value"))
.withColumn("service_type", regexp_extract($"service", """.*(Inbound|Outbound|Outound).*""", 1))
.withColumn("region_type", concat(
when(col("region").isNotNull, col("region")).otherwise(lit("null")), lit(" "),
when(col("service").isNotNull, col("service_type")).otherwise(lit("null"))))
.withColumn("datetime", regexp_extract($"value", """\d{4}-[01]\d-[0-3]\d [0-2]\d:[0-5]\d:[0-5]\d""", 0))
val extractedDF = data.filter(
col("region").isNotNull &&
col("service").isNotNull &&
col("value").isNotNull &&
col("service_type").isNotNull &&
col("region_type").isNotNull &&
col("datetime").isNotNull)
.filter("region != ''")
.filter("service != ''")
.filter("value != ''")
.filter("service_type != ''")
.filter("region_type != ''")
.filter("datetime != ''")
val pathstring = "/user/spark_streaming".concat(args(0))
val query = extractedDF.writeStream
.format("json")
.option("path", pathstring)
.option("checkpointLocation", "/user/some_checkpoint")
.outputMode("append")
.trigger(Trigger.ProcessingTime("5 seconds"))
.start()
query.awaitTermination()
}
}
I need run a single program with both .option("startingOffsets", "latest") and .option("startingOffsets",""" {"someTopic":{"0":438521}}, "someTopic":{"1":438705}}, "someTopic":{"2":254180}}""").
I am not sure if this is achievable

Answer 1

This is an old question at this point, so the OP likely got their answer, but when specifying offsets in JSON string format, you can use -2 for earliest and -1 for latest.
src
The start point when a query is started, either "earliest" which is from the earliest offsets, "latest" which is just from the latest offsets, or a json string specifying a starting offset for each TopicPartition. In the json, -2 as an offset can be used to refer to earliest, -1 to latest. Note: For batch queries, latest (either implicitly or by using -1 in json) is not allowed. For streaming queries, this only applies when a new query is started, and that resuming will always pick up from where the query left off. Newly discovered partitions during a query will start at earliest.