Join Spark Streaming data with lookup data in HDFS
I need to join two tables user and transactions table in Spark Streaming. Currently, I am writing the user table in HDFS.The transactions data will be received in Spark Streaming via Kafka. I need to join this streaming data with users data. The user table may contains modified as well as new records. Currently, I am setting a timer for every 5 minutes and load the HDFS user table data and reloading again this once the timer expires. I also able to find modified records and omitting the older records in user table using timestamp. But within this timer (5 minutes) if any user is created, which wont be present in spark memory, hence they wont be joined with the transactions data. Is there any way to store user data in database and applying joins with streaming data on real time? Any suggestions please
apache-spark
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
add a comment |
I need to join two tables user and transactions table in Spark Streaming. Currently, I am writing the user table in HDFS.The transactions data will be received in Spark Streaming via Kafka. I need to join this streaming data with users data. The user table may contains modified as well as new records. Currently, I am setting a timer for every 5 minutes and load the HDFS user table data and reloading again this once the timer expires. I also able to find modified records and omitting the older records in user table using timestamp. But within this timer (5 minutes) if any user is created, which wont be present in spark memory, hence they wont be joined with the transactions data. Is there any way to store user data in database and applying joins with streaming data on real time? Any suggestions please
apache-spark
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
add a comment |
I need to join two tables user and transactions table in Spark Streaming. Currently, I am writing the user table in HDFS.The transactions data will be received in Spark Streaming via Kafka. I need to join this streaming data with users data. The user table may contains modified as well as new records. Currently, I am setting a timer for every 5 minutes and load the HDFS user table data and reloading again this once the timer expires. I also able to find modified records and omitting the older records in user table using timestamp. But within this timer (5 minutes) if any user is created, which wont be present in spark memory, hence they wont be joined with the transactions data. Is there any way to store user data in database and applying joins with streaming data on real time? Any suggestions please
apache-spark
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
I need to join two tables user and transactions table in Spark Streaming. Currently, I am writing the user table in HDFS.The transactions data will be received in Spark Streaming via Kafka. I need to join this streaming data with users data. The user table may contains modified as well as new records. Currently, I am setting a timer for every 5 minutes and load the HDFS user table data and reloading again this once the timer expires. I also able to find modified records and omitting the older records in user table using timestamp. But within this timer (5 minutes) if any user is created, which wont be present in spark memory, hence they wont be joined with the transactions data. Is there any way to store user data in database and applying joins with streaming data on real time? Any suggestions please
apache-spark
apache-spark
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
asked Nov 19 '18 at 6:52
Gowthaman VGowthaman V
3318
3318
add a comment |
add a comment |
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