Contents

Hadoop prerequisites

Open ports

In a controlled network environment, it is common to have firewall rules in place. In order to enable communication of SAP systems with Hadoop, the following port numbers should be reachable in Hadoop cluster from the SAP system:

These are default port numbers of Hadoop services.

If Kerberos is enabled, KDC (Key Distribution Center) should also be reachable on port 88 (tcp/udp) from each SAP application server.

DNS names

Proper DNS name translation should be configured between SAP and Hadoop for Kerberos communication.

DNS resolution should be tested from SAP host using OS command 'nslookup <hadoop_host_FQDN>'.

If IBM Java is used, also reverse lookup needs to be successful - IP address to hostname.

Hive parameters

Two configuration parameters of the Hive service, which must be configured in Hive Service Advanced Configuration Snippet (Safety Valve) for Hive-site.xml.

hive.exec.dynamic.partition = true
hive.exec.dynamic.partition.mode = nonstrict

Example:

NOTE: If Simba JDBC drivers will be used, these parameters can be set for our session only, therefore without global impact on the cluster.

Hadoop technical user

We recommend to create distinct technical users for every SAP system connected to the Hadoop cluster in order to isolate system's data.
There is usually a central repository for Hadoop users (LDAP/AD), but users can also be created locally (on every Hadoop cluster node).
Recommended naming convention is reflecting SAP <sid>adm users → <sid>hdp

Each Hadoop technical user should have its own dedicated group.

For illustration purposes we will use Hadoop user dvqhdp (with group dvqhdp) in further text.

If Kerberos is used

Create Kerberos principal in form of <sid>hdp@<KERBEROS_REALM>. This can be either a principal created in MIT kerberos, FreeIPA, or an Active Directory user. 
To export a kerberos keytab from Active directory, use following command:

ktpass /princ dvqhdp@HADOOP.LOCAL /pass badpassword1 /ptype KRB5_NT_PRINCIPAL /out DVQ.keytab

HDFS landing zone

A landing zone, typically a home folder of the technical user, needs to be created on HDFS. 

The directory needs to meet following conditions:

• Technical user needs to be able to read and write to this directory and all subdirectories
• Impala and Hive user need to be able to read and write to this directory and all subdirectories

Example landing zone creation:

## Create a home directory
[root@skbtscck21 ~]# hadoop fs -mkdir -p /user/dvqhdp/.Trash
## Set ownership and permissions
[root@skbtscck21 ~]# hadoop fs -chown -R dvqhdp:dvqhdp /user/dvqhdp
[root@skbtscck21 ~]# hadoop fs -chmod -R 770 /user/dvqhdp
## Set ACL to grant access to Hive group (by default containing Hive and Impala user)
[root@skbtscck21 ~]# hadoop fs -setfacl -m default:group:hive:rwx /user/dvqhdp
## Check the directory
[root@skbtscck21 ~]# hadoop fs -ls -d /user/dvqhdp
drwxrwx---+  - dvqhdp dvqhdp	0 2017-03-22 14:45 /user/dvqhdp

Hive database

We recommend to create a dedicated database (schema) in Hive for each SAP system. Recommended database name is sap<sid> (e.g.: sapdvq).

Access privileges on Hadoop side

In the productive Hadoop cluster, depending on Hadoop distribution, either Sentry service or Ranger service is responsible for management of users' privileges on Hadoop resources.
For proper functionality of Datavard Storage Management, the Hadoop technical user <sid>hdp needs access at least to the following two resources:

1. User's HDFS home directory - typically /user/<sid>hdp
2. Assigned Hive database - typically sap<sid>

To set up necessary policies in respective security service, follow the instructions below.

If Sentry is used

Sentry service is managing access to Hadoop resources using Sentry rules. The rules are created for a role, which can have "one to many" relation with user groups (not the users directly).
We typically set up only "one to one" role ↔ group relation. You need to set up two rules, one granting ALL actions on the HDFS directory (gets automatically translated to URI) and one granting all actions on the Hive database.

Example:

NOTE: If HDFS ACL synchronization with Sentry rules is enabled, add the user's directory or any parent directory to the "Sentry Synchronization Path Prefixes" parameter in the HDFS service configuration.
More on HDFS ACL synchronization topic can be found on Synchronizing HDFS ACLs and Sentry Permissions.

If Ranger is used

Similarly to Sentry, Ranger services is managing access to Hadoop resources using policies. The policies can grant privileges either to group or to users directly.
Again, you need to create two policies - one granting full access to Hadoop technical user on his HDFS directory and the other granting access to the Hive database.

HDFS policy example:

Hive database policy example:

Verification of setup

To verify that the setup on Hadoop side is valid, we recommend to use the technical user to create a testing table inside the sap<sid> Hive database.
Load a test file to the user's home directory, verify whether it's there and delete it in the end.
If all the commands are successful, you can conclude that the setup is valid. 

[root@skbtscck21 ~]# database=sapnsq	\\set the database variable
[root@skbtscck21 ~]# jdbc_string="jdbc:hive2://skbtscck21.hadoop.local:10000/$database;principal=hive/skbtscck21.hadoop.local@HADOOP.LOCAL;ssl=true;sslTrustStore=/opt/certs/jks/skbtscck21-keystore.jks;trustStorePassword=123456aB"	\\ set jdbc string
[root@skbtscck21 ~]# kinit -kt ~/nsqhdp.keytab nsqhdp@HADOOP.LOCAL	\\ authenticate as the technical user
[root@skbtscck21 ~]# klist	\\ verify that you have a valid ticket
Ticket cache: FILE:/tmp/krb5cc_0
Default principal: nsqhdp@HADOOP.LOCAL

Valid starting       Expires              Service principal
04/25/2019 17:24:03  04/26/2019 17:24:03  krbtgt/HADOOP.LOCAL@HADOOP.LOCAL
        renew until 05/02/2019 17:24:03
[root@skbtscck21 ~]# beeline -u $jdbc_string -e "create table if not exists $database.xxx (a int)"	\\ Create test table
INFO  : OK                                                                                                         
[root@skbtscck21 ~]# beeline -u $jdbc_string -e "drop table $database.xxx"	\\ delete test table
INFO  : OK
[root@skbtscck21 ~]# beeline -u $jdbc_string -e "show current roles"	\\ only with Sentry - show roles of the user
INFO  : OK
+---------------+--+
|     role      |
+---------------+--+
| sapnsq_admin  |
+---------------+--+
[root@skbtscck21 ~]# beeline -u $jdbc_string -e "show grant role sapnsq_admin"	\\ only with Sentry - display privileges of the role. Should look like the one below
INFO  : OK
+--------------------------------------------------+--------+------------+---------+-----------------+-----------------+------------+---------------+-------------------+----------+--+
|                     database                     | table  | partition  | column  | principal_name  | principal_type  | privilege  | grant_option  |    grant_time     | grantor  |
+--------------------------------------------------+--------+------------+---------+-----------------+-----------------+------------+---------------+-------------------+----------+--+
| sapnsq                                           |        |            |         | sapnsq_admin    | ROLE            | all        | false         | 1490282925235000  | --       |
| hdfs://skbtscck21.hadoop.local:8020/user/nsqhdp  |        |            |         | sapnsq_admin    | ROLE            | all        | false         | 1490282925256000  | --       |
+--------------------------------------------------+--------+------------+---------+-----------------+-----------------+------------+---------------+-------------------+----------+--+

[root@skbtscck21 ~]# echo Success > file.txt	\\ Create a test file
[root@skbtscck21 ~]# hadoop fs -copyFromLocal ./file.txt /user/nsqhdp/	\\ Store file on HDFS
[root@skbtscck21 ~]# hadoop fs -cat /user/nsqhdp/file.txt	\\ Read file
Success
[root@skbtscck21 ~]# hadoop fs -rm -skipTrash /user/nsqhdp/file.txt	\\ Clean up
Deleted /user/nsqhdp/file.txt

OS prerequisites (On SAP host)

This group of requirements relates to the operating systems underlying SAP system with all its application servers. Datavard products (e.g. Datavard Glue, OutBoard DataTiering) have been developed and tested on the SUSE Linux environment and Windows Server 2012, but by design are not limited by the choice of an operating system, if requirements listed in this guide are met. Successful implementations were done also in AIX and Solaris.

Java version 

An up-to-date Java version should be available to the SAP's <sid>adm user. We recommend the latest Java release.

If Hadoop cluster has Kerberos enabled, patched version of Java is required (e.g. Java 8u172).

NOTE: There is a limitation for AIX operating system. Oracle JDK is not available for this platform, thus usual replacement is IBM Java.
This poses certain limitation for Datavard Java Connector, specifically in scenario where Hive connection is facilitated by Zookeeper service. So far the authentication fails when running IBM JRE with Apache Hive driver connecting to Zookeeper. Connection to directly to Hive, or through a loadbalancer with IBM JRE is supported using Simba JDBC drivers.

OS directories

Hadoop connector uses two directories used to store configuration and log files.
Create them with appropriate permissions (read/write) and usual SAP directory ownership (<sid>adm:sapsys).

1. dvd_conn directory in shared /sapmnt filesystem:

   $ ls -ld /sapmnt/DVQ/global/security/dvd_conn
   drwx------ 2 dvqadm sapsys 4096 --- /sapmnt/DVQ/global/security/dvd_conn
   

   This one contains drivers, Kerberos and SSL related files. It is shared among all SAP application servers.

2. dvd_conn directory on each SAP application server:
   

   $ ls -ld /usr/sap/DVQ/DVEBMGS05/work/dvd_conn
   drwxr-xr-x 7 dvqadm sapsys 4096 --- /usr/sap/DVQ/DVEBMGS05/work/dvd_conn

   This one stores Datavard Java Connector libraries, configuration and log files. The folder can be also created automatically during Java connector setup in /DVD/JCO_MNG. 

$ ls -ld /usr/sap/DVQ/dvd_conn
drwxr-xr-x 2 dvqadm sapsys 4096 --- /usr/sap/DVQ/dvd_conn

SAP Java Connector library

SAP Java Connector 3.0 library libsapjco3.so, which can be downloaded from the SAP marketplace, needs to be uploaded to the SAP application server. It should be located in the directory referenced by LD_LIBRARY_PATH environment variable of <sid>adm user.

It is recommended to append a shared Datavard directory (/sapmnt/<SID>/global/security/dvd_conn) to LD_LIBRARY_PATH variable of <sid>adm user and place libsapjco3.so to this directory.
Or you may also copy it directly into the SAP kernel directory, which is by default included in LD_LIBRARY_PATH variable.

$ echo $LD_LIBRARY_PATH
/usr/sap/DVQ/SYS/exe/run:/usr/sap/DVQ/SYS/exe/uc/linuxx86_64:/usr/sap/DVQ/hdbclient:/sapmnt/DVQ/global/security/dvd_conn

/sapmnt/DVQ/global/security/dvd_conn/ # ls -l libsapjco3.so
-rwxr-x--- 1 dvqadm sapsys 59 Apr  5 15:12 libsapjco3.so

JDBC Drivers

JDBC protocol is used to connect to Hadoop services (Hive and Impala). JDBC drivers have to be manually stored on the operating system and be accessible to Datavard connector.
We recommend to store the drivers in the shared dvd_conn directory, organized in sub-directories to avoid possible conflicts.

$ ls -ld /sapmnt/DVQ/global/security/dvd_conn/[hi]*
drwxr-x--- 2 dvqadm sapsys 4096 --- /sapmnt/DVQ/global/security/dvd_conn/hive
drwxr-x--- 3 dvqadm sapsys 4096 --- /sapmnt/DVQ/global/security/dvd_conn/impala

JDBC drivers can be usually downloaded from your Hadoop vendors website.

There are multiple drivers able to facilitate communication between Datavard Java Connector and respective Hadoop service.
Based on our experience, the most reliable are Simba drivers (adopted by Cloudera, Hortonworks and MapR Hadoop distributions).

Kerberos keytab and configuration files

The Kerberos keytab of <sid>hdp principal should be exported from Kerberos database, copied into the operating system directory /sapmnt/DVQ/global/security/dvd_conn and made available to the <sid>adm user:

/sapmnt/DVQ/global/security/dvd_conn # ls -l DVQ.keytab
-r-------- 1 dvqadm sapsys 59 Apr  5 15:12 DVQ.keytab

At the same location, the Kerberos configuration file should be created or copied and made readable for the user <sid>adm.

Usually a suitable krb5.conf file can be found on Hadoop nodes. Here is a sample of Kerberos configuration file:

/sapmnt/DVQ/global/security/dvd_conn # ls -l krb5.conf
-r-------- 1 dvqadm sapsys 393 Feb 22 16:28 krb5.conf

/sapmnt/DVQ/global/security/dvd_conn # cat krb5.conf
[libdefaults]
default_realm = HADOOP.LOCAL
dns_lookup_kdc = false
dns_lookup_realm = false
ticket_lifetime = 86400
renew_lifetime = 604800
forwardable = true
default_tgs_enctypes = rc4-hmac
default_tkt_enctypes = rc4-hmac
permitted_enctypes = rc4-hmac
udp_preference_limit = 1
kdc_timeout = 3000
[realms]
HADOOP.LOCAL = {
kdc = hadoop01.hadoop.local
admin_server = hadoop01.hadoop.local
}

Kerberos keytab verification

To verify that Kerberos config and keytab are valid, execute following steps.

## 	switch to SIDadm
vsks012:~ # su - nsdadm
## change to dvd_conn directory
vsks012:nsdadm 54> cd /sapmnt/NSD/global/security/dvd_conn/	
## check principal in the keytab
vsks012:nsdadm 55> klist -k nsdhdp_cpc.keytab		
Keytab name: FILE:nsdhdp_cpc.keytab
KVNO Principal
---- --------------------------------------------------------------------------
   9 nsdhdp@DATA.DEV

## Set env variable for kerberos config and login as the technical user. This is the expected result
vsks012:nsdadm 56> setenv KRB5_CONFIG /sapmnt/NSD/global/security/dvd_conn/krb5.conf && kinit -kt NSD.keytab nsdhdp@DATA.DEV && klist		 
Ticket cache: FILE:/tmp/krb5cc_1001
Default principal: nsdhdp@DATA.DEV

Valid starting     Expires            Service principal
05/14/19 11:04:08  05/15/19 11:04:08  krbtgt/DATA.DEV@DATA.DEV
        renew until 05/21/19 11:04:08


Kerberos 4 ticket cache: /tmp/tkt1001
klist: You have no tickets cached

SSL Certificates for Java

If your Hadoop cluster has full TLS encryption enabled, it’s necessary to create Java truststore and save it on the following path with correct ownership and permissions:

/sapmnt/<SID>/global/security/dvd_conn # ls -l jssecacerts
-r-------- 1 <SID>adm sapsys 59 Apr  5 15:12 jssecacerts

Server certificates of hosts that Storage Management communicates with or certificate of Certificate Authority that was used to sign these certificates should be placed in this truststore. This is usually Hiveserver2, Impala daemon and HttpFS/WebHDFS service.

An alternative option is to copy the complete jssecacerts truststore from any Hadoop node and place it in this path.

SAP prerequisites

Kerberos cookie encoding

By default, the SAP system encodes certain characters in cookies. The SAP note 1160362 describes the behavior in detail. As the Kerberos cookie must not be anyhow modified for the Kerberos server to accept it, this encoding should be disabled by setting the following parameter in each SAP application server instance profile:

ict/disable_cookie_urlencoding = 1

ict/disable_cookie_urlencoding = 2

The parameter is dynamic starting from the version 7.53.

SAP RFC role and user

The Java connector uses a dedicated user in the SAP system for communication. In our reference configuration, we use the username 'hadoop'. This user should be created with the type 'Communications Data' and with authorizations limiting his privileges to basic RFC communication.

Authorization object required is S_RFC with these settings:

• ACTVT = 16
• RFC_NAME = SYST, RFC1, SDIFRUNTIME
• RFC_TYPE = FUGR

Example of custom SAP role in PFCG transaction (Display Authorization Data):

SSL for SAP RFCs

To enable SSL communication for SAP RFCs, add client certificates of target Hadoop nodes to SAP certificate list in the transaction STRUST.

If HttpFS is used, client certificate of the HttpFS host is required.

If WebHDFS is used, client certificates of all datanodes and namenodes are necessary.

To import necessary certificates:

1. Use the transaction STRUST.
2. In the left menu choose certificate list that you want to add the certificate to (by double-clicking).
3. In the right window area on left bottom click Import.
4. In tab FILE of dialog window point to certificate file on your local file system (certificate should be in .pem format).
5. After you confirm the path and SAP is able to recognize the certificate, details are displayed in the corresponding fields.
6. To complete adding the certificate click Add to Certificate List.
7. Click Save (in general menu or Ctrl+S).
8. Transaction SMICM: top menu > Administration > ICM > Exit Soft > Local/Global.

Check the following parameters (typically they are set and active):

HTTP service and ICM parameters

The HTTP service must be active in SAP system. It can be checked via the transaction SMICM > [Goto] > Services

If the HttpFS/WebHDFS service is SSL secured, HTTPS service needs to be active as well.

The following two parameters are important for the HTTP communication of SAP system:

• icm/HTTP/client/keep_alive_timeout – HTTP communication timeout, can be raised in the case of HTTP communication failing in timeout.
• icm/HTTP/max_request_size_KB – maximum size of data which ICM accepts (default 100 MB).

SAP gateway access

External communication with SAP system goes through the SAP gateway. If SAP system parameter gw/acl_mode is enabled, there are two files (secinfo and reginfo) which limit the access.

In this case two programs need to have granted access either explicitly or by wildcard definition:

• HADOOP_AUTH_CONN
• HADOOP_JAVA_CONN

The program IDs are defined later in this guide within the step Hadoop Storage Setup#RFC Destinations. More information on the SAP gateway ACL topic can be found on the SAP web site Gateway Security Files secinfo and reginfo.

Configuration

When all prerequisites are fulfilled, further configuration is performed from the SAP system.

RFC Destinations

There are three RFC connections which should be created through the transaction SM59.

HttpFS/WebHDFS RFC

Datavard storage management communicates with HDFS using WebHDFS API. In the reference configuration we will be using HttpFS service, but this can be substituted with WebHDFS if necessary.

The only difference in the setup when WebHDFS is used, is the port number and SSL certificates required in STRUST.

This RFC connection is used for communication with Hadoop's HttpFS service which mediates operations in HDFS.

Two RFCs pointing to different HttpFS services can be created to ensure High Availability.

The name and description of the destination is optional, but it is recommended to designate its purpose with keywords 'Hadoop' and 'HttpFS'. In our example, the RFC destination also contains the Hadoop server hosting HttpFS service for the sake of clarity:

Entries explained:

• Connection Type – G for HTTP connection to an external service
• Target host – FQDN of Hadoop server hosting HttpFS service
• Service No. – port number on which HttpFS service is listening (14000 for HttpFS, 50070 for WebHDFS)
• Path Prefix – this string consists of two parts
  1. /webhdfs/v1 part is mandatory
  2. /user/dvqhdp part defines Hadoop user's 'root' directory in HDFS where flat files from SAP system are loaded

If SSL is used: Enable SSL and add client certificate list which is used in Logon & Security tab.

Authentication RFC

This RFC connection is part of the authentication mechanism towards any Hadoop cluster in a kerberized environment. 

The RFC setup is very basic as parameters affecting authentication are defined elsewhere. It is recommended to use the generic RFC name 'HADOOP_AUTH_CONN':

Entries explained:

• Connection Type – T for TCP/IP Connection
• Activation Type – select Registered Server Program
• Program ID – HADOOP_AUTH_CONN

It is important to enable the HADOOP_AUTH_CONN program registration in the SAP gateway (SAP Gateway Access Control Lists).

Java RFC

Java RFC by name refers to the Java service which is used for communication with Hadoop services via JDBC:

Entries explained:

• Connection Type – T for TCP/IP Connection
• Activation Type – select Registered Server Program
• Program ID – HADOOP_JAVA_CONN

It is important to enable the HADOOP_JAVA_CONN program registration in the SAP gateway (SAP Gateway Access Control Lists).

Logical paths and logical filenames

Datavard ships default logical paths leading to files stored on SAP application servers. These default values are usable for most SAP installations and in general don't need be changed. If these default paths are used, administrator needs to make sure that all security related files (kerberos keytab, kerberos config, jssecacerts) and drivers stick to the default naming used in these paths. 

In shipped Datavard paths, standard SAP logical paths DIR_HOME and DIR_GLOBAL are frequently used as variables. These paths usually refer to DIR_HOME = /usr/sap/<SID>/<INSTANCE>/work and DIR_GLOBAL = /sapmnt/<SID>/global/

Logical files and their values shipped by Datavard are following:

• /DVD/DEF_KRB_KEYTAB = <P=DIR_GLOBAL>/security/dvd_conn/<SID>.keytab
• /DVD/DEF_KRB_CONFIG = <P=DIR_GLOBAL>/security/dvd_conn/krb5.config
• /DVD/DEF_SSL_TRUSTSTORE = <P=DIR_GLOBAL>/security/dvd_conn/jssecacerts
• /DVD/DEF_JCO_DIR = <P=DIR_HOME>/dvd_conn/
• /DVD/DEF_HIVE_DRIVER = <P=DIR_GLOBAL>/security/dvd_conn/hive
• /DVD/DEF_IMPALA_DRIVER = <P=DIR_GLOBAL>/security/dvd_conn/impala

If a customer wants to use custom location or filename, a Z copy of these logical paths and logical files with customizations needs to be made, as any direct change to these paths would be overwritten during Storage Management update.

Password hash generator

All passwords that are stored in Storage management need to be hashed upfront using report /DVD/XOR_GEN. This report can be executed using transaction /DVD/RL_EXE 

JCO Management

There are two Java connectors which Storage Management works with. The connector HADOOP_AUTH_CONN is used for the Kerberos authentication and the connector HADOOP_JAVA_CONN runs SQL queries against Hadoop services. These Java connectors run as two independent OS processes and can be controlled through transaction /DVD/JCO_MNG. Current latest versions are 79 for HADOOP_JAVA_CONN (JDBC) and 78 for HADOOP_AUTH_CONN (Kerberos)

This transaction allows the user to link Datavard Java connector to existing SAP RFC created in previous steps, and maintain settings of Datavard java connector. After all required fields are filled and saved, the user can click the Restart button to start the Java service. When the java process is running, the user can control it across application servers and display logs.

Step-by-step:

1. After selecting JCO which settings you want to adjust (double-click in the list of all JCOs), switch to Edit mode 
2. Instead of manually filling all values, you can use the button  or paste previously copied config from clipboard 
3. Adjust values you want to change

   1. Config

      • Client - the client of SAP technical user used to register on SAP gateway

      • RFC User - username of SAP technical user used to register on SAP gateway

      • Password -  hashed password of SAP technical user used to register on SAP gateway, the hash can be created by typing password in the field below and clicking 'Hash' button

      • Program ID - ID used to register Java application on SAP gateway, the value is automatically pulled from RFC that is used

      • Install directory - directory on the application server where the application and log files will be generated - can be a physical path or a logical path enclosed in <>, default path </DVD/DEF_JCO_DIR> can be used. After changing this value you have to click the 'Generate paths' button

      • Java exe - the path to java executable on the SAP application server

      • Java vendor - Name of Java vendor, ORACLE or IBM (for SAP JVM, or OpenJDK, fill ORACLE)

   2. Dependencies

      • select a library which you want to use with JCO

   3. Advanced

      • OS Command for starting java service - name of OS command for starting java service (SM69)
      • OS Command for setting access permissions - name of OS command for setting execution rights (SM69)
      • Max RAM used - a maximum amount of RAM used by java service
      • Additional java starting arguments - additional arguments used to start java service
      • Repository destination - Destination type
      • Work thread MIN - Minimum number of work threads
      • Work thread MAX - Maximum number of work threads
      • Connection count - Number of connections
      • Peak limit - Limit of connections at peak
      • Log4j log level - level of messages collected in logs
      • Log4j log deletion - how long the logs should be archived
      • JAR path - the path where the JAR file will be created
      • Server config path - the path where the server config will be created
      • Destination config path - the path where the destination config will be created
      • Log files path - a directory where the log files will be saved
      • Log4j config path - the path where the log4j config file will be created
4. Go to the 'General' tab and assign an RFC to the java connector
   • RFC Usage - Defines an RFC that points to this java application.
5. Save the settings
6. Start the java service by clicking the 'Restart' button

HttpFS authentication

Table /DVD/HDP_CUS_C contains required authentication information for storages of type Hadoop. Entries in this table are tied to HttpFS RFC created previously.

If 2 HttpFS RFCs were created to support HA scenarios, an entry needs to be created in this table for both of them.

The table can be maintained through the transaction /DVD/RL_TM.

Sample entry:

Entries explained:

• Destination – HttpFS RFC destination created in HttpFS RFC
• User Name – Hadoop user principal 
• Auth. Method – authentication method towards the Hadoop cluster
• Krb. Keytab – logical file definition for Kerberos keytab file, default /DVD/DEF_KRB_KEYTAB can be used
• Krb. Config – logical file definition for Kerberos configuration file, default /DVD/DEF_KRB_CONFIG can be used
• Krb. Service RFC – authentication RFC destination created in Authentication RFC
• SSL Keystore – logical file definition for SSL keystore, default /DVD/DEF_SSL_TRUSTSTORE can be used
• SSL Password – password for accessing SSL keystore, hashed by report /dvd/xor_gen

Storage Management setup

Datavard Storage Management facilitates transparent communication with different types of storages, which includes various types of databases and Hadoop: HDFS for flat files and Hive for structured data.

In order to transparently store data, you should define two types of Hadoop storages in Storage Management:

• HDFS storage which facilitates transfer of files to HDFS through the Hadoop HttpFS service
• Hive storage which enables data replication between SAP tables and Hive tables

The third type of storage is required for efficient querying of data located in Hive:

• Impala storage which connects to Impala agents to provide fast SQL execution by leveraging Impala in-memory data caching

HDFS storage

Create the HDFS storage through the transaction:

/DVD/SM_SETUP > [Edit mode] > [New storage]

Entries explained:

• Storage ID – name of the storage
• Storage Type – choose HADOOP for HDFS
• Description – extended description of the storage for easier identification
• HTTP RFC Destination – HttpFS RFC destination defined in SM59
• HTTP RFC Destination (HA) – Secondary HttpFS RFC destination defined in SM59 as a failover.
• HDFS repeat - Number of retries if request to HDFS is not successful.

Complete the creation of the storage by confirming (F8). If the SAP system can authenticate against Hadoop Kerberos and get properties of HDFS home directory (/user/<sid>hdp) from HttpFS service, storage creation is considered successful.

Hive metastore storage

The Hive metastore storage is created in a similar way as the process of setting up the HDFS storage, but the values are different:

Finish the creation of the storage by confirming (F8). If the SAP system is able to authenticate against Hadoop Kerberos and receives the expected result of the SQL command 'use database', the creation of the storage is considered successful.

Extended explanation for Storage setup with Hadoop distribution other than Cloudera

Following fields' values can differ depending on Hadoop distribution used:

• Load driver classname - apart from Cloudera, there are other vendors offering JDBC drivers able to connect to Hive service (or other Hadoop services like Impala or Drill).
  In case of Hortonworks distribution, the JDBC Hive driver can be found directly on Hadoop node, typically located at /usr/hdp/X.X.X.X-XXXX/hive2/jdbc/hive-jdbc-X.X.X.X-XXXX-standalone.jar.
  The contents of the jar file can be listed with 'less' command:
  

  [root@skbtshcc01 ~]# less /usr/hdp/2.6.4.0-91/hive2/jdbc/hive-jdbc-2.1.0.2.6.4.0-91-standalone.jar | grep HiveDriver
  -rw---- 2.0 fat 6960 bl defN 18-Jan-04 10:39 org/apache/hive/jdbc/HiveDriver.class

  The driver Class Name can be derived from it as

  org.apache.hive.jdbc.HiveDriver

  Reference links:
  https://www.cloudera.com/downloads/connectors/hive/jdbc/2-6-5.html
  https://www.simba.com/resources/jdbc/
  https://www.progress.com/jdbc/apache-hadoop-hive
  http://repo.hortonworks.com/content/repositories/releases/org/apache/hive/hive-jdbc/

  
  
• Custom connection string - not used under standard Cloudera setup, as URL connection string is being composed from other settings. In case of specific configuration on Hadoop side or for testing purposes, it is possible to use explicitly stated conntion URL here.
  Example: connection URL directed at Zookeeper service (port 2181) running on three Hadoop hosts, acting as proxy redirecting connection to currently active Hive server in High Availability setup

  jdbc:hive2://skbtshcc01.hadoop.local:2181,skbtshcc03.hadoop.local:2181,skbtshcc02.hadoop.local:2181/;serviceDiscoveryMode=zooKeeper;zooKeeperNamespace=hiveserver2

  Reference links: 
  https://cwiki.apache.org/confluence/display/Hive/HiveServer2+Clients
  https://www.cloudera.com/documentation/other/connectors/hive-jdbc/latest/Cloudera-JDBC-Driver-for-Apache-Hive-Install-Guide.pdf
  https://docs.microsoft.com/bs-latn-ba/azure/hdinsight/hadoop/apache-hadoop-connect-hive-jdbc-driver?view=aspnetcore-2.1
  https://mapr.com/docs/51/Hive/ConnectingtoHiveServer2-U_29655382-d3e110.html
  
  
• File type - format in which the files loaded to HDFS are stored, depends on Hadoop distribution - in Cloudera and MapR it's typically PARQUET, in Hortonworks it's typically ORC.
  
  
• Compression codec - optional setting, depends on previously selected File Type and whether the files stored in HDFS should be compressed or not. If file type is PARQUET, compression codec is typically SNAPPY, if file type is ORC, compression codec is typically ZLIB.
  
  
• Use Cloudera drivers - depending on this checkbox the default connection URL is generated either with JDBC Cloudera/Simba driver syntax (checkbox ticked), or with JDBC Apache Hive driver syntax (checkbox unticked).
  If custom connection string is used, this should be left unchecked.

Troubleshooting

In the case of any issues with Java connector, you can find the Java logs in application server to determine a source of the issue with the report /DVD/SM_HIVE_DISPLAY_JAVA_LOG.