This will not work the way you have implemented it. The code that you have here
will be called only once before the streaming query is started. Once the
streaming query starts, this code is not called
What I would do is
1. Implement a udf that calculates flourtimestamp
2. Add a column in df2 called “Flourtimestamp”, and populate it with the
flour timestamp using udf.
3. Write the stream using
Df2.writeStream.format(“text”).partitionBy(“flourtimestamp”).option(“path”,
“/home/data”).option("checkpointLocation","./checkpoint").start()
The UDF will be called for every row. And partitionBy will create a folder
within /home/data
From: Swapnil Chougule <the.swapni...@gmail.com>
Date: Friday, June 1, 2018 at 6:21 AM
To: user <user@spark.apache.org>
Subject: Spark structured streaming generate output path runtime
Hi
I want to generate output directory runtime for data. Directory name is derived
from current timestamp.
Lets say, data for same minute should go into same directory.
I tried following snippet but it didn't work. All data is being written in same
directory (created with respect to initial timestamp)
val query = df2.writeStream
.format("text")
.option("path", "/home/data/"+getFlourTimestamp())
.option("checkpointLocation","./checkpoint")
.start()
query.awaitTermination()
def getFlourTimestamp(): Long ={
var curTime = System.currentTimeMillis()
curTime - (curTime % 5000)
}
In other words, I want getFlourTimestamp() to be executed after every batch.
Any help around this will be really appreciated.
Thanks,
Swapnil
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