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 <spark.recei...@gmail.com> 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 >