State of Security: Apache Spark & Apache Zeppelin

1. Director, Product Management
June 30, 2016
Twitter: @neomythos
Vinay Shukla

2. 2 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Thank You

3. 3 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Who Are I?
 Product Management
 Spark for 2.5 + years, Hadoop for 3+ years
 Recovering Programmer
 Blog at www.vinayshukla.com
 Twitter: @neomythos
 Addicted to Yoga, Hiking, & Coffee
 Minor contributor to Apache Zeppelin
Vinay Shukla

4. 4 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Security: Rings of Defense
Perimeter Level Security
•Network Security (i.e. Firewalls)
Data Protection
•Wire encryption
•HDFS TDE/Dare
•Others
Authentication
•Kerberos
•Knox (Other Gateways)
OS Security
Authorization
•Apache Ranger/Sentry
•HDFS Permissions
•HDFS ACLs
•YARN ACL
Page 4

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Key to Spark Security
Spark processes data in-memory, does not store it.
Page 5

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Context: Spark Deployment Modes
• Spark on YARN
–Spark driver (SparkContext) in YARN AM(yarn-cluster)
–Spark driver (SparkContext) in local (yarn-client):
• Spark Shell & Spark Thrift Server runs in yarn-client only
Client
Executor
App
MasterSpark Driver
Client
Executor
App Master
Spark Driver
YARN-Client YARN-Cluster

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Spark on YARN
Spark Submit
John Doe
Spark
AM
Spark
AM
1
Hadoop Cluster
HDFS
Executor
YARN
RM
YARN
RM
4
2 3
Node
Manager

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Spark – Security – Four Pillars
 Authentication
 Authorization
 Audit
 Encryption
Spark leverages Kerberos on YARN
Ensure network is secure

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Authentication: Kerberos Primer
Client
KDC
NN
DN
1. kinit - Login and get Ticket Granting Ticket (TGT)
3. Get NameNode Service Ticket (NN-ST)
2. Client Stores TGT in Ticket
Cache
4. Client Stores NN-ST in Ticket
Cache
5. Read/write file given NN-ST and
file name; returns block locations,
block IDs and Block Access Tokens
if access permitted
6. Read/write block given
Block Access Token and block ID
Client’s
Kerberos
Ticket
Cache

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Kerberos authentication within Spark
KDC
Use Spark ST, submit
Spark Job
Spark gets Namenode (NN)
service ticket
YARN launches Spark
Executors using John
Doe’s identity
Get service ticket for
Spark,
John Doe
Spark AMSpark AM
NNNN
Executor reads from HDFS using
John Doe’s delegation token
kinit
1
2
3
4
5
6
7
Hadoop Cluster

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Spark + X (Source of Data)
KDC
Use Spark ST, submit
Spark Job
Spark gets X ST
YARN launches Spark
Executors using John
Doe’s identity
Get Service Ticket (ST)
for Spark
Spark AMSpark AM
XX
Executor reads from X using John
Doe’s delegation token
kinit
1
2
3
4
5
6
7
Hadoop Cluster
John Doe

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Spark – Kerberos - Example
kinit -kt /etc/security/keytabs/johndoe.keytab johndoe@
EXAMPLE.COM
./bin/spark-submit --class org.apache.spark.examples.SparkPi
--master yarn-cluster --num-executors 3 --driver-memory 512m
--executor-memory 512m --executor-cores 1 lib/spark-
examples*.jar 10

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HDFS
Spark – Authorization
YARN Cluster
A B C
KDC
Use Spark ST,
submit Spark Job
Get Namenode (NN)
service ticket
Executors
read from
HDFS
Client gets service
ticket for Spark
RangerRangerCan John launch this job?
Can John read this file
John Doe

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Encryption: Spark – Communication Channels
Spark
Submit
RM
Shuffle
Service
AM
Driver
NM
Ex 1 Ex N
Shuffle Data
Control/RPC
Shuffle
BlockTransfer
Data
Source
Read/Write
Data
FS – Broadcast,
File Download

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Spark Communication Encryption Settings
Shuffle Data
Control/RPC
Shuffle
BlockTransfer
Read/Write
Data
FS – Broadcast,
File Download
spark.authenticate.enableSaslEncryption= true
spark.authenticate = true. Leverage YARN to distribute keys
Depends on Data Source, For HDFS RPC (RC4 | 3DES) or SSL for WebHDFS
NM > Ex leverages YARN based SSL
spark.ssl.enabled = true

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Gotchas with Spark Security
 Client -> Spark Thrift Server > Spark Executors – No identity propagation on 2nd
hop
– Lowers security, forces STS to run as Hive user to read all data
– Use SparkSQL via shell or programmatic API
– https://issues.apache.org/jira/browse/SPARK-5159
 Spark + HBase with Kerberos
– Issue fixed in Spark 1.4 (Spark-6918)
 Spark Stream + Kafka + Kerberos
– Issues fixed in HDP 2.4.x
– No SSL support yet
 Spark jobs > 72 Hours
– Delegation token not renewed before Spark 1.4
 Spark Shuffle > Only SASL, no SSL support

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How can I get Row/Column/Masking with SparkSQL?
 Hopefully you went to “Fine Grained Security for Hive & Spark” yesterday

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Key Features: Spark Column Security with LLAP
 Fine-Grained Column Level Access Control for SparkSQL.
 Fully dynamic policies per user. Doesn’t require views.
 Use Standard Ranger policies and tools to control access and masking policies.
Flow:
1.SparkSQL gets data locations
known as “splits” from HiveServer
and plans query.
2.HiveServer2 authorizes access
using Ranger. Per-user policies like
row filtering are applied.
3.Spark gets a modified query plan
based on dynamic security policy.
4.Spark reads data from LLAP.
Filtering / masking guaranteed by
LLAP server.
HiveServer2
Authorization
Hive Metastore
Data Locations
View Definitions
LLAP
Data Read
Filter Pushdown
Ranger Server
Dynamic Policies
Spark Client
1
2
4
3

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Example: Per-User Row Filtering by Region in SparkSQL
Spark User 2
(East Region)
Spark User 1
(West Region)
Original Query:
SELECT * from CUSTOMERS
WHERE total_spend > 10000
Query Rewrites based on
Dynamic Ranger Policies
LLAP Data Access
User ID Region Total Spend
1 East 5,131
2 East 27,828
3 West 55,493
4 West 7,193
5 East 18,193
Dynamic Rewrite:
SELECT * from CUSTOMERS
WHERE total_spend > 10000
AND region = “east”
Dynamic Rewrite:
SELECT * from CUSTOMERS
WHERE total_spend > 10000
AND region = “west”

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Interacting with Spark
Ex
Spark on YARN
Zeppelin
Spark-
Shell
Ex
Spark
Thrift
Server
Driver
REST
ServerDriver
Driver
Driver

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Apache Zeppelin Security

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Apache Zeppelin: Authentication + SSL
Spark on YARN
Ex Ex
LDAP
John Doe
1
2
3
SSL
Firewall

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Zeppelin + Livy E2E Security
Zeppelin
Spark
Yarn
Livy
Ispark Group
Interpreter
SPNego: Kerberos Kerberos/RPC
Livy APIs
LDAP
John Doe
Job runs as John Doe

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Apache Zeppelin: Authorization
 Notebook level authorization
 Grant Permissions (Owner, Reader, Writer) to users/groups on Notebooks
 LDAP Group integration just got merged (ZEPPELIN-946)

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Thank You
Vinay Shukla
@neomythos