Requirements

Minimum requirements

The minimum requirements allow loading datasets of only up to 50 million RDF triples.

  • 2 gigabytes of memory

  • 2 gigabytes of disk space

  • Java SE Development Kit 8, 11, or 12 (not required for GraphDB Free desktop installation)

Warning

All GraphDB indexes are optimized for hard disks with very low seek time. Our team highly recommend using only SSD partition for persisting repository images.

Hardware sizing

The best approach for correctly sizing the hardware resources is to estimate the number of explicit statements. Statistically, an average dataset has 3:1 statements to unique RDF resources. The total number of statements determines the expected repository image size, and the number of unique resources affects the memory footprint required to initialize the repository.

The table below summarizes the recommended parameters for planning RAM and disk sizing:

  • Statements are the planned number of explicit statements.

  • Unique resources are the expected number of unique RDF resources (IRIs, blank nodes, literals, RDF-star [formerly RDF*] embedded triples).

  • Java heap (minimal) is the minimal recommend JVM heap required to operate the database controlled by -Xmx parameter.

  • Java heap (optimal) is the recommended JVM heap required to operate a database controlled by -Xmx parameter.

  • Off heap is the database memory footprint (outside of the JVM heap) required to initialize the database.

  • OS is the recommended minimal space reserved for the operating system.

  • Total is the RAM required for the hardware configuration.

  • Repository image is the expected size on disk. For repositories with inference use the total number of explicit + implicit statements.

Statements

Unique resources

Java heap (min)

Java heap (opt)

Off heap

OS

Total

Repository image

100M

33.3M

1.2GB

3.6GB

370M

2

6GB

12GB

200M

66.6M

2.4GB

7.2GB

740M

3

11GB

24GB

500M

166.5M

6GB

18GB

1.86GB

4

24GB

60GB

1B

333M

12GB

30GB

3.72GB

4

38GB

120GB

2B

666M

24GB

30GB

7.44GB

4

42GB

240GB

5B

1.665B

30GB

30GB

18.61GB

4

53GB

600GB

10B

3.330B

30GB

30GB

37.22GB

4

72GB

1200GB

20B

6.660B

30GB

30GB

74.43GB

4

109GB

2400GB

Memory management

The optimal approach towards memory management of GraphDB is based on a balance of performance and resource availability per repository. In heavy use cases such as parallel importing into a number of repositories, GraphDB may take up more memory than usual.

There are several configuration properties with which the amount of memory used by GraphDB can be controlled:

  • Reduce the global cache: by default, it can take up to half of the available memory allocated to GraphDB, which during periods of stress can be critical. By reducing the size of the cache, more memory can be freed up for the actual operations. This can be beneficial during periods of prolonged imports as that data is not likely to be queried right away.

    graphdb.page.cache.size=2g

  • Reduce the buffer size: this property is used to control the amount of statements that can be stored in buffers by GraphDB. By default, it is sized at 200,000 statements, which can impact memory usage if many repositories are actively reading/writing data at once. The optimal buffer size depends on the hardware used, as reducing it would cause more write/read operations to the actual storage.

    pool.buffer.size=50000

  • Reduce inference pool size: this property controls the number of available inference workers that are used for forward inferencing during import to repositories. Reducing the number of inference workers can have a limited benefit, depending on the number of available CPU cores as per the GraphDB license. For the table below, we have used an 8-core license and reduced the number of workers per repository down to three.

    infer.pool.size=3

  • Disable parallel import: during periods of prolonged imports to a large number of repositories, parallel imports can take up more than 800 megabytes of retained heap per repository. In such cases, parallel importing can be disabled, which would force data to be imported serially to each repository. However, serial import reduces performance.

    graphdb.engine.parallel-import=false

This table shows an example of retained heap usage by repository, using different configuration parameters:

Configurations

Retained heap per repository

During prolonged import

Stale

Default

≥800MB

340MB

+ Reduced global cache (2GB)

670MB

140MB

+ Reduced buffer size*

570-620MB

140MB

+ Reduced inference pool size*

370-550MB

140MB

Serial import**

210-280MB

140MB

* Depends on the number of available CPU cores to GraphDB. For the statistics, the default buffer size was reduced from 200,000 (default) to 50,000 statements. The inference pool size was reduced from eight to three. Keep in mind that this reduces performance.

** Without reducing buffer and inference pool sizes. Disables parallel import, which impacts performance.

Licensing

GraphDB EE is available under an RDBMS-like commercial license on a per-server-CPU basis. It is neither free nor open source. To purchase a license or obtain a copy for evaluation, please contact graphdb-info@ontotext.com.