I am new to using Apache NiFi, and I trying to create a template that takes a JSON file and turns it into a set of SQL insert statements.
So far I have created a template that takes the JSON file and I have got it to the point of PutSQL. There is no database to connect to at the moment, but what I have not been able to check is the output. Can this be done? What I need to check is whether the array of JSON has been turned into a INSERT per element in the array
As far as inpecting the output, what does your flow look like? If you have something like ConvertJSONToSQL -> PutSQL, you can leave PutSQL stopped and run ConvertJSONToSQL, then you will see FlowFile(s) in the connection between the two processors. Then you can right-click on the connection and choose List Queue, then click the "eye" icon on the right for the FlowFile you wish to inspect. That will show you the contents of the FlowFile right before it goes into PutSQL.
Having said all that, if your JSON file contains fields that correspond to columns in your database, consider PutDatabaseRecord instead of ConvertJSONToSQL -> PutSQL. That can use a JsonTreeReader to parse each record, and it will generate and execute the necessary SQL as a prepared statement using the values in all records of the FlowFile. That way you don't need to generate the SQL yourself or worry about fragmented transactions or any of that.
Related
I a beginner in data warehousing and apache nifi. I was trying taking the Mysql table data into nifi and then want to put that data into another mysql database table, I am successfully getting data from the database table one and I can also able to print that data into file using putFile processor.
But now I want to store that queued data into mysql database table, I know there is putSQL processor but it was not working for me.
Can anyone let me know how to do it correctly.
Here are the screenshots of my flow
PutSQL configuration-
I converted data from Avro to JSON and then JSON to SQL in case if that would work, but this also not worked.
Use PutDatabaseRecord and remove the Convert* processors.
From nifi docs:
The PutDatabaseRecord processor uses a specified RecordReader to input
(possibly multiple) records from an incoming flow file. These records
are translated to SQL statements and executed as a single transaction.
If any errors occur, the flow file is routed to failure or retry, and
if the records are transmitted successfully, the incoming flow file is
routed to success. The type of statement executed by the processor is
specified via the Statement Type property, which accepts some
hard-coded values such as INSERT, UPDATE, and DELETE, as well as 'Use
statement.type Attribute', which causes the processor to get the
statement type from a flow file attribute. IMPORTANT: If the Statement
Type is UPDATE, then the incoming records must not alter the value(s)
of the primary keys (or user-specified Update Keys). If such records
are encountered, the UPDATE statement issued to the database may do
nothing (if no existing records with the new primary key values are
found), or could inadvertently corrupt the existing data (by changing
records for which the new values of the primary keys exist).
This should be more performant and cleaner.
This is a relatively simple problem with (I'm hoping) a similarly-simple solution.
In my ADF ETLs, any time there's a known and expected yet unrecoverable row-based error, I don't want my full ETL to fail. Instead, I'd rather pipe those rows off to a log, which I can then pick up at the end of the ETL for manual inspection. To do this, I use conditional splits.
Most of the time, there shouldn't be any rows like this. When this is the case, I don't want my blob sink to write a file. However, the current behavior writes a file no matter what -- it's just that the file only contains the table header.
Is there a way to skip writing anything to a blob sink when there are no input rows?
Edit: Somehow I forgot to specify -- I'm specifically referring to a Mapping Data Flow with a blob sink.
You can use Lookup activity(don't check first row only) to get all your table data firstly. Then use If condition to check the count of Lookup activity's output. If its count > 0, execute next activity(or data flow).
Would it be possible to route flow files according to the result of an SQL query which returns a single row result? For example, if the result is '1' the flow file will be processed; otherwise, it will be ignored.
Solution
The following approach worked best for me.
Use ExecuteSQL processor in order to run filtering SQL query. The query was written to produce either a single record (match) or an empty record set (no match) in a way suggested by Shu.
Connect ExecuteSQL to RouteOnAttribute processor in order to filter out unmatched flow files using the following value of routing property value ${executesql.row.count:replaceNull(0):gt(0)}
Notice, that the original content of a flow file will be lost after applying ExecuteSQL. It's not an issue in my case, because I do filtering before processing flow file content and my SQL query is based entirely on the flow file attributes and not on its content. Though in a more general scenario, when the flow file content is modified by the incoming part of the flow, one should save file content somewhere (e.g. file system) and restore it after the filtering part has applied.
You can add where clause in your sql query where <field_name> = 1 then we are only going to have output a flowfile when the result value =1.
(or)
Checking the data in NiFi:
We are going to have AVRO format data as the result of SQL query so you can use
option1:ConvertAvroToJson Processor:
Convert the AVRO data into JSON format then extract the value from the json content as attribute using EvaluateJsonPath processor.
Then use RouteOnAttribute processor add new property using NiFi expression language equals function compare the value and route the flowfile to matched relation.
Refer to this link more details regards to EvaluateJsonpath and RouteOnAttribute processor configs.
option2: Using QueryRecord processor:
By using QueryRecord processor we can run SQL queries on the content of the flowfile
Add new property to the processor as
select * from FLOWFILE where <filed_name> =1
Feed the property relation to the other processor
Refer to this link for more details regarding QueryRecord processor usage.
I am getting files from remote server using Nifi: my files are as follow:
timestamp (ms), nodeID,value
12345,x,12.4
12346,x,12.7
12348,x,13.4
12356,x,13,6
12355,y,12.0
I am now just get and fetch and split lines and send them to Kafka, but before hand, I need to apply a checksum approach on my records and aggregate them based on time stamp, what I need to do to add an additional column to my content and count the records based on aggregated time stamps, for example aggregation based on each 10 milliseconds and nodeID..
timestamp (ms), nodeID,value, counts
12345,x,12.4,3
12346,x,12.7,3
12348,x,13.4,3
12356,x,13,6,1
12355,y,12.0,1
How to do above process in NiFi. I am totally new to Nifi but need to add above functinality to my Nifi process. I am currently using below nifi process
This may not answer your question directly, but you should consider refactoring your flow to use the "record" processors. It would greatly simplify things and would probably get you closer to being able to do the aggregation.
The idea is to not split up the records, and instead process them in place. Given your current flow, the 4 processors after FetchSFTP would like change to a single ConvertRecord processor that converts CSV to JSON. You would first need to defined a simple Avro schema for your data.
Once you have the record processing setup, you might be able to use PartitionRecord to partition the records by the node id, and then from there the missing piece would be how to count by the timestamps.
Some additional resources...
https://blogs.apache.org/nifi/entry/record-oriented-data-with-nifi
https://bryanbende.com/development/2017/06/20/apache-nifi-records-and-schema-registries
https://www.slideshare.net/BryanBende/apache-nifi-record-processing
I have a JSON flow-file and I need determine if I should be doing an INSERT or UPDATE. The trick is to only update the columns that match the JSON attributes. I have an ExecuteSQL working and it returns executesql.row.count, however I've lose the original JSON flow-file which I was planing to use as a routeonattribute. I'm trying to get the MergeContent to join the ExecuteSQL (dump the Avro output, I only need the executesql.row.count attribute) with the JSON flow. I've set follow before I do the ExecuteSQL:
fragment.count=2
fragment.identifier=${UUID()}
fragment.index=${nextInt()}
Alternatively I could create a MERGE, if there is a way to loop through the list of JSON attributes that match the Oracle table?
How large is your JSON? If it's small, you might consider using ExtractText (matching the whole document) to get the JSON into an attribute. Then you can run ExecuteSQL, then ReplaceText to put the JSON back into the content (overwriting the Avro results). If your JSON is large, you could set up a DistributedMapCacheServer and (in a separate flow) run ExecuteSQL and store the value or executesql.row.count into the cache. Then in the JSON flow you can use FetchDistributedMapCache with the "Put Cache Value In Attribute" property set.
If you only need the JSON to use RouteOnAttribute, perhaps you could use EvaluateJsonPath before ExecuteSQL, so your conditions are already in attributes and you can replace the flow file contents.
If you want to use MergeContent, you can set fragment.count to 2, but rather than using the UUID() function, you could set "parent.identifier" to "${uuid}" using UpdateAttribute, then DuplicateFlowFile to create 2 copies, then UpdateAttribute to set "fragment.identifier" to "${parent.identifier}" and "fragment.index" to "${nextInt():mod(2)}". This gives a mergeable set of two flow files, you can route on fragment.index being 0 or 1, sending one to ExecuteSQL and one through the other flow, joining back up at MergeContent.
Another alternative is to use ConvertJSONToSQL set to "UPDATE", and if it fails, route those flow files to another ConvertJSONToSQL processor set to "INSERT".