Valid from 5.3
The documentation below is valid from Datafari v5.3 upwards
First of all : Do not underestimate the importance of SWAP memory ! Be sure your SWAP fits the recommandations according to your physical memory !
We recommend a minimum of
1,5 time the amount of RAM as SWAP memory for servers that have less than 32 GB of RAM
1 time the amount of RAM as SWAP memory for servers that have 32 GB of RAM and more
Note that if you server is properly sized in terms of RAM, you should almost never see any usage of SWAP. This recommended minimum amount is a safety measure in case you end up in scenarii where you push your Datafari to the limit of your physical hardware.
The stability and performances of Datafari mainly rely on a good RAM management and its proper distribution between its components. Adding more RAM to a Datafari server is completely useless if you do not configure it to exploit the available RAM !
IF YOU WANT TO SEE THE DEFAULT VALUES: You can check the default JVM RAM configuration of Datafari CE in monoserver_community_memory.properties , the same applies for the Datafari EE version (some properties do not have the same configuration as for the CE edition).
CASE 1: Configuration priori to the first start of your Datafari
Before the first start of Datafari, you can modify in one place all of the values of RAM that you want to apply for the different components.
This file is located in : $DATAFARI_HOME/bin/deployUtils/
You need to edit the file corresponding to your installation case, for example if you are using the Community Edition of Datafari, edit the file monoserver_community_memory.properties.
There is a line of each component, for example if you want to change the amount of RAM for Solr edit the property :
SOLRMEMORY=1g
Your modifications will be taken account only if Datafari has never been initialized before.
CASE 2: Configuration in case you had already started your Datafari at least once before
If your Datafari is already initialized, here are the files location and the parameters to adjust the JVM RAM (excluding SWAP!) consumption by component :
(You need to restart Datafari for the changes to be applied)
Component | File location | Parameter |
|---|---|---|
Solr | DATAFARI_HOME/solr/bin/solr.in.sh | SOLR_JAVA_MEM (-Xms and -Xmx) |
ManifoldCF | DATAFARI_HOME/mcf/mcf_home/option.env.unix | -Xms and -Xmx |
Tomcat (Main) | DATAFARI_HOME/tomcat/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) |
Tomcat (MCF) | DATAFARI_HOME/tomcat-mcf/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) |
Cassandra | DATAFARI_HOME/cassandra/conf/jvm-server.options | -Xms and -Xmx |
PostgreSQL | DATAFARI_HOME/pgsql/data/postgresql.conf | shared_buffers |
Apache Zeppelin | DATAFARI_HOME/analytic-stack/zeppelin/bin/common.sh | ZEPPELIN_MEM (-Xms and -Xmx) ZEPPELIN_INTP_MEM (-Xms and -Xmx) |
Logstash | DATAFARI_HOME/analytic-stack/logstash/config/jvm.options | -Xms and -Xmx |
Tika server | DATAFARI_HOME/tika-server/conf/tika-config.xml | In the <forkedJvmArgs> section: |
As a reminder, the "Xms" parameter defines the minimum amount of RAM consumption and the "Xmx" parameter the maximum ! It is highly recommended to have the same value for those two parameters.
The more important thing to know is that there are two main resource consumption sources : the crawl and the search
Crawl
During a crawl phase, the component that will need a lot of RAM is Tika, because it extracts the content of documents and needs, for certain doc types, to fully load them in memory. Depending on your job configuration, Tika may be :
Used in MCF if your job is configured to use the "TikaServerRmetaConnector" transformation connector
Used in Solr if your job is configured to use the "DatafariSolr" output connector instead of the "DatafariSolrNoTika" output connector
Used in its own JVM if your job is configured to use the "TikaServer" transformation connector (only available in the Enterprise edition)
If you used the Simplified MCF UI of Datafari to create your job, it is automatically configured with the "TikaOCR" connector for the Community Edition, and the "TikaServer" connector for the Enterprise Edition.
Knowing this, you will need to allocate more RAM to the component that handle Tika to ensure the stability of your crawls. Tika needs at least 5GB to be stable. So if you use Tika into MCF or into Solr, you will need to add 5GB to the default configuration of those components.
Search
During the search phase a lot of RAM may be used by Solr to improve performances. Solr uses its own JVM allocated RAM but it also relies on the system cache to perform searches, so it is important to NOT allocate all the available physical memory to Solr or any other Datafari component to ensure best performances !
We recommend to allocate between at least 1GB of RAM and a maximum of 12GB of RAM to Solr depending on the available RAM of your Server. For best search performances, try to let a number of un-allocated RAM that matches your Solr index size (size of the DATAFARI_HOME/solr/solr_home directory).
Note about Solr memory : By default, its value is set to 1 GB. If you encounter OOMs and you have enough spare ram, try increasing it (keep in mind that your system needs enough SWAP space as well)
Valid from 5.1
The documentation below is valid from Datafari v5.1 upwards
First of all : Do not underestimate the importance of SWAP memory ! Be sure your SWAP fits the recommandations according to your physical memory !
We recommend a minimum of
- 1,5 time the amount of RAM as SWAP memory for servers that have less than 32 GB of RAM
- 1 time the amount of RAM as SWAP memory for servers that have 32 GB of RAM and more
Note that if you server is properly sized in terms of RAM, you should almost never see any usage of SWAP. This recommended minimum amount is a safety measure in case you end up in scenarii where you push your Datafari to the limit of your physical hardware.
The stability and performances of Datafari mainly rely on a good RAM management and its proper distribution between its components. Adding more RAM to a Datafari server is completely useless if you do not configure it to exploit the available RAM !
You can check the default JVM RAM configuration of Datafari CE in monoserver_community_memory.properties
CASE 1: Configuration priori to the first start of your Datafari
Before the first start of Datafari, you can modify in one place all of the values of RAM that you want to apply for the different components.
This file is located in : $DATAFARI_HOME/bin/deployUtils/
You need to edit the file corresponding to your installation case, for example if you are using the Community Edition of Datafari, edit the file monoserver_community_memory.properties.
There is a line of each component, for example if you want to change the amount of RAM for Solr edit the property :
SOLRMEMORY=1g
Your modifications will be taken account only if Datafari has never been initialized before.
CASE 2: Configuration in case you had already started your Datafari at least once before
If your Datafari is already initialized, here are the files location and the parameters to adjust the JVM RAM (excluding SWAP!) consumption by component :
(You need to restart Datafari for the changes to be applied)
Component | File location | Parameter |
|---|---|---|
Solr | DATAFARI_HOME/solr/bin/solr.in.sh | SOLR_JAVA_MEM (-Xms and -Xmx) |
ManifoldCF | DATAFARI_HOME/mcf/mcf_home/option.env.unix | -Xms and -Xmx |
Tomcat (Main) | DATAFARI_HOME/tomcat/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) |
Tomcat (MCF) | DATAFARI_HOME/tomcat-mcf/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) |
Cassandra | DATAFARI_HOME/cassandra/conf/jvm-server.options | -Xms and -Xmx |
PostgreSQL | DATAFARI_HOME/pgsql/data/postgresql.conf | shared_buffers |
Elasticsearch | DATAFARI_HOME/elk/elasticsearch/config/jvm.options | -Xms and -Xmx |
Logstash | DATAFARI_HOME/elk/logstash/config/jvm.options | -Xms and -Xmx |
Kibana | DATAFARI_HOME/elk/scripts/set-elk-env.sh | NODE_OPTIONS (--max-old-space-size) |
Tika server | DATAFARI_HOME/tika-server/bin/set-tika-env.sh | TIKA_SPAWN_MEM (-JXms and -JXmx) |
As a reminder, the "Xms" parameter defines the minimum amount of RAM consumption and the "Xmx" parameter the maximum ! It is highly recommended to have the same value for those two parameters.
The more important thing to know is that there are two main resource consumption sources : the crawl and the search
Crawl
During a crawl phase, the component that will need a lot of RAM is Tika, because it extracts the content of documents and needs, for certain doc types, to fully load them in memory. Depending on your job configuration, Tika may be :
Used in MCF if your job is configured to use the "TikaServerRmetaConnector" transformation connector
Used in Solr if your job is configured to use the "DatafariSolr" output connector instead of the "DatafariSolrNoTika" output connector
Used in its own JVM if your job is configured to use the "TikaServer" transformation connector (only available in the Enterprise edition)
If you used the Simplified MCF UI of Datafari to create your job, it is automatically configured with the "TikaOCR" connector for the Community Edition, and the "TikaServer" connector for the Enterprise Edition.
Knowing this, you will need to allocate more RAM to the component that handle Tika to ensure the stability of your crawls. Tika needs at least 5GB to be stable. So if you use Tika into MCF or into Solr, you will need to add 5GB to the default configuration of those components.
Search
During the search phase a lot of RAM may be used by Solr to improve performances. Solr uses its own JVM allocated RAM but it also relies on the system cache to perform searches, so it is important to NOT allocate all the available physical memory to Solr or any other Datafari component to ensure best performances !
We recommend to allocate between at least 1GB of RAM and a maximum of 12GB of RAM to Solr depending on the available RAM of your Server. For best search performances, try to let a number of un-allocated RAM that matches your Solr index size (size of the DATAFARI_HOME/solr/solr_home directory).
Note about Solr memory : By default, its value is set to 1 GB. If you encounter OOMs and you have enough spare ram, try increasing it (keep in mind that your system needs enough SWAP space as well)
Valid from 5.0
The documentation below is valid from Datafari v5.0 upwards
First of all : Do not underestimate the importance of SWAP memory ! Be sure your SWAP fits the recommandations according to your physical memory !
You can find recommandations in your operating system documentation and/or website
The stability and performances of Datafari mainly rely on a good RAM management and distribution between its components. Adding more RAM to a Datafari server is completely useless if you don't configure it to exploit the available RAM !
You can check the default RAM configuration of Datafari in the Software requirements
Here are the files location and parameters that allow you to adjust the JVM RAM (excluding SWAP!) consumption by component :
Component | File location | Parameter | Default values |
|---|---|---|---|
Solr | DATAFARI_HOME/solr/bin/solr.in.sh | SOLR_JAVA_MEM (-Xms and -Xmx) | 1GB |
ManifoldCF | DATAFARI_HOME/mcf/mcf_home/option.env.unix | -Xms and -Xmx | 3.5GB |
Tomcat (Main) | DATAFARI_HOME/tomcat/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) | 1GB |
Tomcat (MCF) | DATAFARI_HOME/tomcat-mcf/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) | 1GB |
Cassandra | DATAFARI_HOME/cassandra/conf/jvm-server.options | -Xms and -Xmx | 1GB |
PostgreSQL | DATAFARI_HOME/pgsql/data/postgresql.conf | shared_buffers | 1GB |
Elasticsearch | DATAFARI_HOME/elk/elasticsearch/config/jvm.options | -Xms and -Xmx | 1GB |
Logstash | DATAFARI_HOME/elk/logstash/config/jvm.options | -Xms and -Xmx | 1GB |
Kibana | DATAFARI_HOME/elk/scripts/set-elk-env.sh | NODE_OPTIONS (--max-old-space-size) | 1.4GB (maximum size) |
Tika server (Enterprise Edition) | DATAFARI_HOME/tika-server/bin/set-tika-env.sh | TIKA_SPAWN_MEM (-JXms and -JXmx) | 5.6GB |
As a reminder, the "Xms" parameter defines the minimum amount of RAM consumption and the "Xmx" parameter the maximum ! It is highly recommended to have the same value for those two parameters.
The more important thing to know is that there are two main resource consumption sources : the crawl and the search
Crawl
During a crawl phase, the component that will need a lot of RAM is Tika, because it extracts the content of documents and needs, for certain doc types, to fully load them in memory. Depending on your job configuration, Tika may be :
Used in MCF if your job is configured to use the "TikaOCR" transformation connector
Used in Solr if your job is configured to use the "DatafariSolr" output connector instead of the "DatafariSolrNoTika" output connector
Used in its own JVM if your job is configured to use the "TikaServer" transformation connector (only available in the Enterprise edition)
If you used the Simplified MCF UI of Datafari to create your job, it is automatically configured with the "TikaOCR" connector for the Community Edition, and the "TikaServer" connector for the Enterprise Edition.
Knowing this, you will need to allocate more RAM to the component that handle Tika to ensure the stability of your crawls. Tika needs at least 5GB to be stable. So if you use Tika into MCF or into Solr, you will need to add 5GB to the default configuration of those components.
Search
During the search phase a lot of RAM may be used by Solr to improve performances. Solr uses its own JVM allocated RAM but it also relies on the system cache to perform searches, so it is important to NOT allocate all the available physical memory to Solr or any other Datafari component to ensure best performances !
We recommend to allocate between at least 1GB of RAM and a maximum of 12GB of RAM to Solr depending on the available RAM of your Server. For best search performances, try to let a number of un-allocated RAM that matches your Solr index size (size of the DATAFARI_HOME/solr/solr_home directory).
Note about Solr memory : By default, its value is set to 1 GB. If you encounter OOMs and you have enough spare ram, try increasing it (keep in mind that your system needs enough SWAP space as well)
Valid from 4.0
The documentation below is valid from Datafari v4.0.0 upwards
First of all : Do not underestimate the importance of SWAP memory ! Be sure your SWAP fits the recommandations according to your physical memory !
You can find recommandations in your operating system documentation and/or website
The stability and performances of Datafari mainly rely on a good RAM management and distribution between its components. Adding more RAM to a Datafari server is completely useless if you don't configure it to exploit the available RAM !
You can check the default RAM configuration of Datafari in the Software requirements
Here are the files location and parameters that allow you to adjust the JVM RAM (excluding SWAP!) consumption by component :
Component | File location | Parameter | Example for 8GB of RAM (not SWAP) |
|---|---|---|---|
Solr | DATAFARI_HOME/solr/bin/solr.in.sh | SOLR_JAVA_MEM (-Xms and -Xmx) | 1GB |
ManifoldCF | DATAFARI_HOME/mcf/mcf_home/option.env.unix | -Xms and -Xmx | 3.5GB |
Tomcat (Main) | DATAFARI_HOME/tomcat/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) | 1GB |
Tomcat (MCF) | DATAFARI_HOME/tomcat-mcf/bin/setenv.sh | CATALINA_OPTS (-Xms and -Xmx) | 1GB |
Cassandra | DATAFARI_HOME/cassandra/conf/jvm.options | -Xms and -Xmx | 1GB |
Elasticsearch | DATAFARI_HOME/elk/elasticsearch/config/jvm.options | -Xms and -Xmx | N/A |
Logstash | DATAFARI_HOME/elk/logstash/config/jvm.options | -Xms and -Xmx | N/A |
Kibana | DATAFARI_HOME/elk/scripts/set-elk-env.sh | NODE_OPTIONS (--max-old-space-size) | N/A |
Tika server (Enterprise Edition) | DATAFARI_HOME/tika-server/bin/set-tika-env.sh | TIKA_SPAWN_MEM (-JXms and -JXmx) | N/A |
As a reminder, the "Xms" parameter defines the minimum amount of RAM consumption and the "Xmx" parameter the maximum ! It is highly recommended to have the same value for those two parameters.
The more important thing to know is that there are two main resource consumption sources : the crawl and the search
Crawl
During a crawl phase, the component that will need a lot of RAM is Tika, because it extracts the content of documents and needs, for certain doc types, to fully load them in memory. Depending on your job configuration, Tika may be :
Used in MCF if your job is configured to use the "TikaOCR" transformation connector
Used in Solr if your job is configured to use the "DatafariSolr" output connector instead of the "DatafariSolrNoTika" output connector
Used in its own JVM if your job is configured to use the "TikaServer" transformation connector (only available in the Enterprise edition)
If you used the Simplified MCF UI of Datafari to create your job, it is automatically configured with the "TikaOCR" connector for the Community Edition, and the "TikaServer" connector for the Enterprise Edition.
Knowing this, you will need to allocate more RAM to the component that handle Tika to ensure the stability of your crawls. Tika needs at least 5GB to be stable. So if you use Tika into MCF or into Solr, you will need to add 5GB to the default configuration of those components.
Search
During the search phase a lot of RAM may be used by Solr to improve performances. Solr uses its own JVM allocated RAM but it also relies on the system cache to perform searches, so it is important to NOT allocate all the available physical memory to Solr or any other Datafari component to ensure best performances !
We recommend to allocate between at least 1GB of RAM and a maximum of 12GB of RAM to Solr depending on the available RAM of your Server. For best search performances, try to let a number of un-allocated RAM that matches your Solr index size (size of the DATAFARI_HOME/solr/solr_home directory).
Default RAM standard requirements (SWAP NOT INCLUDED):
Monoserver (Community edition, without OCR) for a machine with 8GB of RAM :
Tomcat : 1 GB
Solr : 1 GB
ManifoldCF : 3.5GB
Cassandra : 1 GB
PostgreSQL : 1 GB
Monoserver (Enterprise edition)
Tomcat : 1 GB
Solr : 1 GB
ManifoldCF : 256MB
Cassandra : 1 GB
PostgreSQL : 1 GB
ELK : 2 GB Elastic
Tika-server : 5 Go