Building Data Pipelines for Solr with Apache NiFi

© Hortonworks Inc. 2011 – 2015. All Rights Reserved
Building Data Pipelines for Solr with
Apache NiFi
Bryan Bende – Member of Technical Staff

Outline
• Introduction to Apache NiFi
• Solr Indexing & Update Handlers
• NiFi/Solr Integration
• Use Cases

About Me
• Member of Technical Staff at Hortonworks
• Apache NiFi Committer & PMC Member since June 2015
• Solr/Lucene user for several years
• Developed Solr integration for Apache NiFi 0.1.0 release
• Twitter: @bbende / Blog: bryanbende.com

Introduction
Installing Solr and getting started - easy (extract, bin/solr start)
Defining a schema and configuring Solr - easy
Getting all of your incoming data into Solr - not as easy
A lot of time spent…
• Cleaning and parsing data
• Writing custom code/scripts
• Building approaches for monitoring and debugging
• Deploying updates to code/scripts for small changes
Need something to make this easier…

Introduction to Apache NiFi

Apache NiFi
• Powerful and reliable system to process and
distribute data
• Directed graphs of data routing and transformation
• Web-based User Interface for creating, monitoring,
& controlling data flows
• Highly configurable - modify data flow at runtime,
dynamically prioritize data
• Data Provenance tracks data through entire
system
• Easily extensible through development of custom
components
[1] https://nifi.apache.org/

NiFi - Terminology
FlowFile
• Unit of data moving through the system
• Content + Attributes (key/value pairs)
Processor
• Performs the work, can access FlowFiles
Connection
• Links between processors
• Queues that can be dynamically prioritized
Process Group
• Set of processors and their connections
• Receive data via input ports, send data via output ports

NiFi - User Interface
• Drag and drop processors to build a flow
• Start, stop, and configure components in real time
• View errors and corresponding error messages
• View statistics and health of data flow
• Create templates of common processor & connections

NiFi - Provenance
• Tracks data at each point as it flows
through the system
• Records, indexes, and makes
events available for display
• Handles fan-in/fan-out, i.e. merging
and splitting data
• View attributes and content at given
points in time

NiFi - Queue Prioritization
• Configure a prioritizer per
connection
• Determine what is important for your
data – time based, arrival order,
importance of a data set
• Funnel many connections down to a
single connection to prioritize across
data sets
• Develop your own prioritizer if
needed

NiFi - Extensibility
Built from the ground up with extensions in mind
Service-loader pattern for…
• Processors
• Controller Services
• Reporting Tasks
• Prioritizers
Extensions packaged as NiFi Archives (NARs)
• Deploy NiFi lib directory and restart
• Provides ClassLoader isolation
• Same model as standard components

NiFi - Architecture
OS/Host
JVM
Flow Controller
Web Server
Processor 1 Extension N
FlowFile
Repository
Content
Repository
Provenance
Repository
Local Storage
OS/Host
JVM
Flow Controller
Web Server
FlowFile
Repository
Content
Repository
Provenance
Repository
Local Storage
OS/Host
JVM
NiFi Cluster Manager – Request Replicator
Web Server
Master
NiFi Cluster
Manager (NCM)
OS/Host
JVM
Flow Controller
Web Server
FlowFile
Repository
Content
Repository
Provenance
Repository
Local Storage
Slaves
NiFi Nodes

Solr Indexing & Update Handlers

Solr – Indexing Data
Update Handlers
• XML, JSON, CSV
• https://cwiki.apache.org/confluence/display/solr/Uploading+Data+with+Index+Handlers
Clients
• Java, PHP, Python, Ruby, Scala, Perl, and more
• https://wiki.apache.org/solr/IntegratingSolr

Solr Update Handlers - XML
Adding documents
<add>
<doc>
<field name=”foo”>bad</field>
</doc>
</add>
Deleting documents
<delete>
<id>1234567</id>
<query>foo:bar</query>
</delete>
Other Operations
<commit waitSearcher="false"/>
<commit waitSearcher="false"
expungeDeletes="true"/>
<optimize waitSearcher="false"/>

Solr Update Handlers - JSON
Solr-Style JSON…
Add Documents
[
{
"id": "1”,
"title": "Doc 1”
},
{
"id": "2”,
"title": "Doc 2”
}
]
Commands
{
"add": {
"doc": {
"id": "1”,
"title": {
"boost": 2.3,
"value": "Doc1”
}
}
}
}

Solr Update Handlers - JSON
Custom JSON
• Transform custom JSON based on Solr
schema
• Define paths to split JSON into multiple Solr
documents
• Field mappings from JSON field name to
Solr field name
Produces two Solr documents:
- John, Math, term1, 90
- John, Biology, term1, 86
split=/exams&
f=name:/name&
f=subject:/exams/subject&
f=test:/exams/test&
f=marks:/exams/marks
{
"name": "John",
"exams": [
{
"subject": "Math",
"test" : "term1",
"marks" : 90},
{
"subject": "Biology",
"test" : "term1",
"marks" : 86}
]
}

Solr Update Handlers - CSV
/update with Content-Type:application/csv
Important parameters:
• separator
• trim
• header
• fieldnames
• skip
• rowid

SolrJ Client
SolrDocument Update
SolrInputDocument doc =
new SolrInputDocument();
doc.addField("first", "bob");
doc.addField("last", "smith");
solrClient.add(doc);
ContentStream Update
ContentStreamUpdateRequest request =
new ContentStreamUpdateRequest(
"/update/json/docs");
request.setParam("json.command", "false");
request.setParam("split", "/exams");
request.getParams().add("f", "name:/name");
request.getParams().add("f",
"subject:/exams/subject");
request.getParams().add("f","test:/exams/test");
request.getParams().add("f","marks:/exams/marks");
request.addContentStream(new ContentStream...);

NiFi/Solr Integration

NiFi Solr Processors
• Support Solr Cloud and stand-alone Solr instances
• Leverage SolrJ – CloudSolrClient & HttpSolrClient
• Extract new documents based on a date/time field – GetSolr
• Stream FlowFile content to an update handler - PutSolrContentStream

PutSolrContentStream
• Choose Solr Type - Cloud or
Standard
• Specify ZooKeeper hosts, or the
Solr URL
• Specify a collection if using Solr
Cloud
• Specify the Solr path for the
ContentStream
• Dynamic properties sent as
key/value pairs on the request
• Relationships for success, failure,
and connection_failure

GetSolr
• Solr Type, Solr Location, and
Collection are the same as PutSolr
• Specify a query to run on each
execution of the processor
• Specify a sort clause and a date
field used to filter results
• Schedule processor to run on a
cron, or timer
• Retrieves documents with ‘Date
Field’ greater than time of last
execution
• Produces output in SolrJ XML

Use Cases

Use Cases – Index JSON
1. Pull in Tweets using Twitter API
2. Extract language and text into FlowFile
attributes
3. Get non-empty English tweets
${twitter.text:isEmpty():not():and(
${twitter.lang:equals("en")})}
4. Merge together JSON documents based on
quantity, or time
5. Use dynamic field mappings to select fields for
indexing:

Use Cases – Issue Commands
1. Generate a FlowFile on a cron, or timer, to
initiate an action
2. Replace the contents of the FlowFile with a
Solr command
<delete>
<query>
timestamp:[* TO NOW-1HOUR]
</query>
</delete>
3. Send the command to the appropriate
update handler

Use Cases – Multiple Collections
1. Set a FlowFile attribute
containing the name of a Solr
collection
2. Use expression language when
setting the Collection property on
the Solr processor:
${solr.collection}
Note:
• If merging documents, merge per
collection in this case
• Current bug preventing this scenario
from working:
https://issues.apache.org/jira/browse/NIFI-959

Use Cases – Log Aggregation
1. Listen for log events over UDP on a
given port
• Set ‘Flow File Per Datagram’ to true
2. Send JSON log events
• Syslog UDP forwarding
• Logback/log4j UDP appenders
3. Merge JSON events together based on
size, or time
4. Stream JSON update to Solr
http://bryanbende.com/development/2015/05/17/c
ollecting-logs-with-apache-nifi/

Use Cases – Index Avro
1. Receive an Avro datafile with binary
encoding
2. Convert Avro to JSON using built in
ConvertAvroToJSON processor
3. Stream JSON documents to Solr

Use Cases – Index a Relational Database
1. GenerateFlowFile acts a timer to trigger
ExecuteSQL
(Future plans to not require in an incoming FlowFile
to ExecuteSQL NIFI-932)
2. ExecuteSQL performs a SQL query and
streams the results as an Avro datafile
Use expression language to construct a dynamic
date range:
${now():toNumber():minus(60000)
:format(‘YYYY-MM-DD’}
3. Convert Avro to JSON using built in
ConvertAvroToJSON processor
4. Stream JSON update to Solr

Use Case – Extraction in a Cluster
1. Schedule GetSolr to run
on Primary Node
2. Send results to a Remote
Process Group pointing
back to self
3. Data gets redistributed to
“Solr XML Docs” Input
Ports across cluster
4. Perform further
processing on each node

Future Work
Unofficial ideas…
PutSolrDocument
• Parse FlowFile InputStream into one or more SolrDocuments
• Allow developers to provide “FlowFile to SolrDocument” converter
PutSolrAttributes
• Create a SolrDocument from FlowFile attributes
• Processor properties specify attributes to include/exclude
Distribute & Execute Solr Commands
• DistributeSolrCommand learns about Solr shards and produces commands per shard
• ExecuteSolrCommand performs action based on the incoming command

Summary
Resources
• Apache NiFi Mailing Lists
– https://nifi.apache.org/mailing_lists.html
• Apache NiFi Documentation
– https://nifi.apache.org/docs.html
• Getting started developing extensions
– https://cwiki.apache.org/confluence/display/NIFI/Maven+Projects+for+Extensions
– https://nifi.apache.org/developer-guide.html
Contact Info:
• Email: bbende@hortonworks.com
• Twitter: @bbende

Sources
[1] https://nifi.apache.org/
[2] https://cwiki.apache.org/confluence/display/solr/Uploading+Data+with+Index+Handlers
[3] https://wiki.apache.org/solr/IntegratingSolr
[4] http://lucidworks.com/blog/indexing-custom-json-data/

Thank you

Building Data Pipelines for Solr with Apache NiFi

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