I think if you don't cache the jdbc table, then it should auto-refresh.
On Mon, Nov 13, 2017 at 1:21 PM, spark receiver <[email protected]>
wrote:
> Hi
>
> I’m using struct streaming(spark 2.2) to receive Kafka msg ,it works
> great. The thing is I need to join the Kafka message with a relative static
> table stored in mysql database (let’s call it metadata here).
>
> So is it possible to reload the metadata table after some time
> interval(like daily ) without restart running struct streaming?
>
> Snippet code as following :
>
> // df_meta contains important information to join with the dataframe read
> from kafka
>
> val df_meta = spark.read.format("jdbc").option("url", mysql_url).option(
> "dbtable", "v_entity_ap_rel").load()
>
> df_meta.cache()
>
> val df = spark.readStream
> .format("kafka")
> .option("kafka.bootstrap.servers",
> *“*x.x.x.x:9092").option("fetch.message.max.bytes",
> "50000000").option("kafka.max.partition.fetch.bytes", "50000000")
> .option("subscribe", "rawdb.raw_data")
> .option("failOnDataLoss", true)
> .option("startingOffsets", "latest")
> .load()
> .select($"value".as[Array[Byte]])
> .map(avroDeserialize(_))
> .as[ApRawData].select("APMAC", "RSSI", "sourceMacAddress", "updatingTime")
> .join(df_meta.as("b"), $"a.apmac" === $"b.apmac*”*)
>
>
> df.selectExpr("ENTITYID", "CLIENTMAC", "STIME", "case when a.rrssi>=b.rssi
> then '1' when a.rrssi < b.nearbyrssi then '3' else '2' end FLAG",
> "substring(stime,1,13) STIME_HOUR")
> .distinct().writeStream.format("parquet").partitionBy("STIME_HOUR")
> .option("checkpointLocation",
> "/user/root/t_cf_table_chpt").trigger(ProcessingTime("5 minutes"))
> .start("T_CF_TABLE")
> .awaitTermination()
>
>
> Mason
>
