Using SAP HANA Cloud for Production
This guide is available for Node.js and Java.
Use the toggle in the title bar or press v to switch.
SAP HANA Cloud is supported as the CAP standard database and recommended for productive use with full support for schema evolution and multitenancy.
WARNING
CAP isn't validated with other variants of SAP HANA, like "SAP HANA Database as a Service" or "SAP HANA (on premise)".
Setup & Configuration
Run this to use SAP HANA Cloud for production:
npm add @cap-js/hana
Using other SAP HANA drivers...
Package @cap-js/hana
uses the hdb
driver by default. You can override that by running npm add @sap/hana-client
, thereby adding it to your package dependencies, which then takes precedence over the default driver.
Prefer cds add
... as documented in the deployment guide, which also does the equivalent of npm add @cap-js/hana
but in addition cares for updating mta.yaml
and other deployment resources.
To use SAP HANA Cloud, configure a module, which includes the feature cds-feature-hana
. For example, add a Maven runtime dependency to the cds-feature-hana
feature:
<dependency>
<groupId>com.sap.cds</groupId>
<artifactId>cds-feature-hana</artifactId>
<scope>runtime</scope>
</dependency>
TIP
The modules cds-starter-cloudfoundry
and cds-starter-k8s
include cds-feature-hana
.
The datasource for HANA is then auto-configured based on available service bindings of type service-manager and hana.
Learn more about the configuration of an SAP HANA Cloud Database
Running cds build
Deployment to SAP HANA is done via the SAP HANA Deployment Infrastructure (HDI) which in turn requires running cds build
to generate all the deployable HDI artifacts. For example, run this in cap/samples/bookshop:
cds build --for hana
Which should display this log output:
[cds] - done > wrote output to:
gen/db/init.js
gen/db/package.json
gen/db/src/gen/.hdiconfig
gen/db/src/gen/.hdinamespace
gen/db/src/gen/AdminService.Authors.hdbview
gen/db/src/gen/AdminService.Books.hdbview
gen/db/src/gen/AdminService.Books_texts.hdbview
gen/db/src/gen/AdminService.Currencies.hdbview
gen/db/src/gen/AdminService.Currencies_texts.hdbview
gen/db/src/gen/AdminService.Genres.hdbview
gen/db/src/gen/AdminService.Genres_texts.hdbview
gen/db/src/gen/CatalogService.Books.hdbview
gen/db/src/gen/CatalogService.Books_texts.hdbview
gen/db/src/gen/CatalogService.Currencies.hdbview
gen/db/src/gen/CatalogService.Currencies_texts.hdbview
gen/db/src/gen/CatalogService.Genres.hdbview
gen/db/src/gen/CatalogService.Genres_texts.hdbview
gen/db/src/gen/CatalogService.ListOfBooks.hdbview
gen/db/src/gen/data/sap.capire.bookshop-Authors.csv
gen/db/src/gen/data/sap.capire.bookshop-Authors.hdbtabledata
gen/db/src/gen/data/sap.capire.bookshop-Books.csv
gen/db/src/gen/data/sap.capire.bookshop-Books.hdbtabledata
gen/db/src/gen/data/sap.capire.bookshop-Books.texts.csv
gen/db/src/gen/data/sap.capire.bookshop-Books.texts.hdbtabledata
gen/db/src/gen/data/sap.capire.bookshop-Genres.csv
gen/db/src/gen/data/sap.capire.bookshop-Genres.hdbtabledata
gen/db/src/gen/localized.AdminService.Authors.hdbview
gen/db/src/gen/localized.AdminService.Books.hdbview
gen/db/src/gen/localized.AdminService.Currencies.hdbview
gen/db/src/gen/localized.AdminService.Genres.hdbview
gen/db/src/gen/localized.CatalogService.Books.hdbview
gen/db/src/gen/localized.CatalogService.Currencies.hdbview
gen/db/src/gen/localized.CatalogService.Genres.hdbview
gen/db/src/gen/localized.CatalogService.ListOfBooks.hdbview
gen/db/src/gen/localized.sap.capire.bookshop.Authors.hdbview
gen/db/src/gen/localized.sap.capire.bookshop.Books.hdbview
gen/db/src/gen/localized.sap.capire.bookshop.Genres.hdbview
gen/db/src/gen/localized.sap.common.Currencies.hdbview
gen/db/src/gen/sap.capire.bookshop.Authors.hdbtable
gen/db/src/gen/sap.capire.bookshop.Books.hdbtable
gen/db/src/gen/sap.capire.bookshop.Books_author.hdbconstraint
gen/db/src/gen/sap.capire.bookshop.Books_currency.hdbconstraint
gen/db/src/gen/sap.capire.bookshop.Books_foo.hdbconstraint
gen/db/src/gen/sap.capire.bookshop.Books_genre.hdbconstraint
gen/db/src/gen/sap.capire.bookshop.Books_texts.hdbtable
gen/db/src/gen/sap.capire.bookshop.Genres.hdbtable
gen/db/src/gen/sap.capire.bookshop.Genres_parent.hdbconstraint
gen/db/src/gen/sap.capire.bookshop.Genres_texts.hdbtable
gen/db/src/gen/sap.common.Currencies.hdbtable
gen/db/src/gen/sap.common.Currencies_texts.hdbtable
Generated HDI Artifacts
As we see from the log output cds build
generates these deployment artifacts as expected by HDI, based on CDS models and .csv files provided in your projects:
.hdbtable
files for entities.hdbview
files for views / projections.hdbconstraint
files for database constraints.hdbtabledata
files for CSV content- a few technical files required by HDI, such as
.hdinamespace
and.hdiconfig
Custom HDI Artifacts
In addition to the generated HDI artifacts, you can add custom ones by adding according files to folder db/src
. For example, let's add an index for Books titles...
Add a file
db/src/sap.capire.bookshop.Books.hdbindex
and fill it with this content:sqlINDEX sap_capire_bookshop_Books_title_index ON sap_capire_bookshop_Books (title)
Run cds build again → this time you should see this additional line in the log output:
log[cds] - done > wrote output to: [...] gen/db/src/sap.capire.bookshop.Books.hdbindex
Learn more about HDI Design-Time Resources and Build Plug-ins
Deploying to SAP HANA
There are two ways to include SAP HANA in your setup: Use SAP HANA in a hybrid mode, meaning running your services locally and connecting to your database in the cloud, or running your whole application on SAP Business Technology Platform. This is possible either in trial accounts or in productive accounts.
To make the following configuration steps work, we assume that you've provisioned, set up, and started, for example, your SAP HANA Cloud instance in the trial environment. If you need to prepare your SAP HANA first, see How to Get an SAP HANA Cloud Instance for SAP Business Technology Platform, Cloud Foundry environment to learn about your options.
Prepare for Production
To prepare the project, execute:
cds add hana --for hybrid
This configures deployment for SAP HANA to use the hdbtable and hdbview formats. The configuration is added to a [hybrid]
profile in your package.json.
The profile hybrid
relates to the hybrid testing scenario
If you want to prepare your project for production and use the profile production
, read the Deploy to Cloud Foundry guide.
No further configuration is necessary for Node.js. For Java, see the Use SAP HANA as the Database for a CAP Java Application tutorial for the rest of the configuration.
Using cds deploy
for Ad-Hoc Deployments
cds deploy
lets you deploy just the database parts of the project to an SAP HANA instance. The server application (the Node.js or Java part) still runs locally and connects to the remote database instance, allowing for fast development roundtrips.
Make sure that you're logged in to Cloud Foundry with the correct target, that is, org and space. Then in the project root folder, just execute:
cds deploy --to hana
To connect to your SAP HANA Cloud instance use
cds watch --profile hybrid
.
Behind the scenes, cds deploy
does the following:
- Compiles the CDS model to SAP HANA files (usually in gen/db, or db/src/gen)
- Generates .hdbtabledata files for the CSV files in the project. If a .hdbtabledata file is already present next to the CSV files, no new file is generated.
- Creates a Cloud Foundry service of type
hdi-shared
, which creates an HDI container. Also, you can explicitly specify the name like so:cds deploy --to hana:<myService>
. - Starts
@sap/hdi-deploy
locally. If you need a tunnel to access the database, you can specify its address with--tunnel-address <host:port>
. - Stores the binding information with profile
hybrid
in the .cdsrc-private.json file of your project. You can use a different profile with parameter--for
. With this information,cds watch
/run
can fetch the SAP HANA credentials at runtime, so that the server can connect to it.
Specify --profile
when running cds deploy
as follows:
cds deploy --to hana --profile hybrid
Based on these profile settings, cds deploy
executes cds build
and also resolves additionally binding information. If a corresponding binding exists, its service name and service key are used. The development profile is used by default.
Learn more about the deployment using HDI.Learn more about hybrid testing using service bindings to Cloud services.
If you run into issues, see the Troubleshooting guide.
Deploy Parameters
When using the option --to hana
, you can specify the service name and logon information in several ways.
cds deploy --to hana
In this case the service name and service key either come from the environment variable VCAP_SERVICES
or are defaulted from the project name, for example, myproject-db
with myproject-db-key
. Service instances and key either exist and will be used, or otherwise they're created.
cds deploy --to hana:myservice
This overwrites any information coming from environment variables. The service name myservice
is used and the current Cloud Foundry client logon information is taken to connect to the system.
cds deploy --vcap-file someEnvFile.json
This takes the logon information and the service name from the someEnvFile.json
file and overwrite any environment variable that is already set.
cds deploy --to hana:myservice --vcap-file someEnvFile.json
This is equivalent to cds deploy --to hana:myservice
and ignores information coming from --vcap-file
. A warning is printed after deploying.
Using cf deploy
or cf push
See the Deploying to Cloud Foundry guide for information about how to deploy the complete application to SAP Business Technology Platform, including a dedicated deployer application for the SAP HANA database.
Native SAP HANA Features
The HANA Service provides dedicated support for native SAP HANA features as follows.
Vector Embeddings
Vector embeddings are numerical representations that capture important features and semantics of unstructured data - such as text, images, or audio. This representation makes vector embeddings of similar data have high similarity and low distance to each other. These properties of vector embeddings facilitate tasks like similarity search, anomaly detection, recommendations and Retrieval Augmented Generation (RAG). Vector embeddings from a vector datastore such as the SAP HANA Cloud Vector Engine can help get better generative AI (GenAI) results. This is achieved when the embeddings are used as context to the large language models (LLMs) prompts.
Typically vector embeddings are computed using an embedding model. The embedding model is specifically designed to capture important features and semantics of a specific type of data, it also determines the dimensionality of the vector embedding space. Unified consumption of embedding models and LLMs across different vendors and open source models is provided via the SAP Generative AI Hub.
In CAP, vector embeddings are stored in elements of type cds.Vector:
entity Books : cuid {
title : String(111);
description : LargeString;
embedding : Vector(1536); // vector space w/ 1536 dimensions
}
At runtime, you can compute the similarity and distance of vectors in the SAP HANA vector store using the cosineSimilarity
and l2Distance
(Euclidean distance) functions in queries:
let embedding; // vector embedding as string '[0.3,0.7,0.1,...]';
let similarBooks = await SELECT.from('Books')
.where`cosine_similarity(embedding, to_real_vector(${embedding})) > 0.9`
// Vector embedding of text, for example, from SAP GenAI Hub or via LangChain4j
float[] embedding = embeddingModel.embed(bookDescription).content().vector();
Result similarBooks = service.run(Select.from(BOOKS).where(b ->
CQL.cosineSimilarity(b.embedding(), CQL.vector(embedding)).gt(0.9)));
Learn more about Vector Embeddings in CAP Java
Geospatial Functions
CDS supports the special syntax for SAP HANA geospatial functions:
entity Geo as select from Foo {
geoColumn.ST_Area() as area : Decimal,
new ST_Point(2.25, 3.41).ST_X() as x : Decimal
};
Learn more in the SAP HANA Spatial Reference.
Spatial Grid Generators
SAP HANA Spatial has some built-in grid generator table functions. To use them in a CDS model, first define corresponding facade entities in CDS.
Example for function ST_SquareGrid
:
@cds.persistence.exists
entity ST_SquareGrid(size: Double, geometry: hana.ST_GEOMETRY) {
geom: hana.ST_GEOMETRY;
i: Integer;
j: Integer;
}
Then the function can be called, parameters have to be passed by name:
entity V as select
from ST_SquareGrid(size: 1.0, geometry: ST_GeomFromWkt('Point(1.5 -2.5)'))
{ geom, i, j };
Functions Without Arguments
SAP HANA allows to omit the parentheses for functions that don't expect arguments. For example:
entity Foo { key ID : UUID; }
entity Bar as select from Foo {
ID, current_timestamp
};
Some of which are well-known standard functions like current_timestamp
in the previous example, which can be written without parentheses in CDS models. However, there are many unknown ones, that aren't known to the compiler, for example:
current_connection
current_schema
current_transaction_isolation_level
current_utcdate
current_utctime
current_utctimestamp
sysuuid
To use these in CDS models, you have to add the parentheses so that CDS generic support for using native features can kick in:
entity Foo { key ID : UUID; }
entity Bar as select from Foo {
ID, current_timestamp,
sysuuid() as sysid
};
Regex Functions
CDS supports SAP HANA Regex functions (locate_regexpr
, occurrences_regexpr
, replace_regexpr
, and substring_regexpr
), and SAP HANA aggregate functions with an additional order by
clause in the argument list. Example:
locate_regexpr(pattern in name from 5)
first_value(name order by price desc)
Restriction: COLLATE
isn't supported.
For other functions, where the syntax isn't supported by the compiler (for example, xmltable(...)
), a native .hdbview can be used. See Using Native SAP HANA Artifacts for more details.
HDI Schema Evolution
CAP supports database schema updates by detecting changes to the CDS model when executing the CDS build. If the underlying database offers built-in schema migration techniques, compatible changes can be applied to the database without any data loss or the need for additional migration logic. Incompatible changes like deletions are also detected, but require manual resolution, as they would lead to data loss.
Change | Detected Automatically | Applied Automatically |
---|---|---|
Adding fields | Yes | Yes |
Deleting fields | Yes | No |
Renaming fields | n/a 1 | No |
Changing datatype of fields | Yes | No |
Changing type parameters | Yes | Yes |
Changing associations/compositions | Yes | No 2 |
Renaming associations/compositions | n/a 1 | No |
Renaming entities | n/a | No |
1 Rename field or association operations aren't detected as such. Instead, corresponding ADD and DROP statements are rendered requiring manual resolution activities.
2 Changing targets may lead to renamed foreign keys. Possibly hard to detect data integrity issues due to non-matching foreign key values if target key names remain the same (for example "ID").
No support for incompatible schema changes
Currently there's no framework support for incompatible schema changes that require scripted data migration steps (like changing field constraints NULL > NOT NULL). However, the CDS build does detect those changes and renders them as non-executable statements, requesting the user to take manual resolution steps. We recommend avoiding those changes in productive environments.
Schema Evolution and Multitenancy/Extensibility
There's full support for schema evolution when the cds-mtxs library is used for multitenancy handling. It ensures that all schema changes during base-model upgrades are rolled out to the tenant databases.
WARNING
Tenant-specific extensibility using the cds-mtxs library isn't supported yet Right now, you can't activate extensions on entities annotated with @cds.persistence.journal
.
Schema Updates with SAP HANA
All schema updates in SAP HANA are applied using SAP HANA Deployment Infrastructure (HDI) design-time artifacts, which are auto-generated during CDS build execution.
Schema updates using .hdbtable deployments are a challenge for tables with large data volume. Schema changes with .hdbtable are applied using temporary table generation to preserve the data. As this could lead to long deployment times, the support for .hdbmigrationtable artifact generation has been added. The Migration Table artifact type uses explicit versioning and migration tasks. Modifications of the database table are explicitly specified in the design-time file and carried out on the database table exactly as specified. This saves the cost of an internal table-copy operation. When a new version of an already existing table is deployed, HDI performs the migration steps that haven't been applied.
Deploy Artifact Transitions as Supported by HDI
Current format | hdbcds | hdbtable | hdbmigrationtable |
---|---|---|---|
hdbcds | yes | n/a | |
hdbtable | n/a | yes | |
hdbmigrationtable | n/a | Yes |
WARNING
Direct migration from .hdbcds to .hdbmigrationtable isn't supported by HDI. A deployment using .hdbtable is required up front.
Learn more in the Enhance Project Configuration for SAP HANA Cloud section.
During the transition from .hdbtable to .hdbmigrationtable you have to deploy version=1 of the .hdbmigrationtable artifact, which must not include any migration steps.
HDI supports the hdbcds → hdbtable → hdbmigrationtable migration flow without data loss. Even going back from .hdbmigrationtable to .hdbtable is possible. Keep in mind that you lose the migration history in this case. For all transitions you want to execute in HDI, you need to specify an undeploy allowlist as described in HDI Delta Deployment and Undeploy Allow List in the SAP HANA documentation.
Moving From .hdbcds To .hdbtable
There a migration guide providing you step-by-step instructions for making the switch.
Enabling hdbmigrationtable Generation for Selected Entities During CDS Build
If you're migrating your already deployed scenario to .hdbmigrationtable deployment, you've to consider the remarks in Deploy Artifact Transitions as Supported by HDI.
By default, all entities are still compiled to .hdbtable and you only selectively choose the entities for which you want to build .hdbmigrationtable by annotating them with @cds.persistence.journal
.
Example:
namespace data.model;
@cds.persistence.journal
entity LargeBook {
key id : Integer;
title : String(100);
content : LargeString;
}
CDS build generates .hdbmigrationtable source files for annotated entities as well as a last-dev/csn.json source file representing the CDS model state of the last build.
These source files have to be checked into the version control system.
Subsequent model changes are applied automatically as respective migration versions including the required schema update statements to accomplish the new target state. There are cases where you have to resolve or refactor the generated statements, like for reducing field lengths. As they can't be executed without data loss (for example, String(100)
-> String(50)
), the required migration steps are only added as comments for you to process explicitly.
Example:
>>>> Manual resolution required - DROP statements causing data loss are disabled
>>>> by default.
>>>> You may either:
>>>> uncomment statements to allow incompatible changes, or
>>>> refactor statements, e.g. replace DROP/ADD by single RENAME statement
>>>> After manual resolution delete all lines starting with >>>>>
-- ALTER TABLE my_bookshop_Books DROP (title);
-- ALTER TABLE my_bookshop_Books ADD (title NVARCHAR(50));
Changing the type of a field causes CDS build to create a corresponding ALTER TABLE statement. Data type conversion rules are applied by the SAP HANA database as part of the deployment step. This may cause the deployment to fail if the column contents can't be converted to the new format.
Examples:
- Changing the type of a field from String to Integer may cause tenant updates to fail if existing content can't be converted.
- Changing the type of a field from Decimal to Integer can succeed, but decimal places are truncated. Conversion fails if the content exceeds the maximum Integer length.
We recommend keeping .hdbtable deployment for entities where you expect low data volume. Every .hdbmigrationtable artifact becomes part of your versioned source code, creating a new migration version on every model change/build cycle. In turn, each such migration can require manual resolution. You can switch large-volume tables to .hdbmigrationtable at any time, keeping in mind that the existing .hdbtable design-time artifact needs to be undeployed.
TIP
Sticking to .hdbtable for the actual application development phase avoids lots of initial migration versions that would need to be applied to the database schema.
CDS build performs rudimentary checks on generated .hdmigrationtable files:
- CDS build fails if inconsistencies are encountered between the generated .hdbmigrationtable files and the last-dev/csn.json model state. For example, the last migration version not matching the table version is such an inconsistency.
- CDS build fails if manual resolution comments starting with
>>>>>
exist in one of the generated .hdbmigrationtable files. This ensures that manual resolution is performed before deployment.
Native Database Clauses
Not all clauses supported by SQL can directly be written in CDL syntax. To use native database clauses also in a CAP CDS model, you can provide arbitrary SQL snippets with the annotations @sql.prepend
and @sql.append
. In this section, we're focusing on schema evolution specific details.
Schema evolution requires that any changes are applied by corresponding ALTER statements. See ALTER TABLE statement reference for more information. A new migration version is generated whenever an @sql.append
or @sql.prepend
annotation is added, changed, or removed. ALTER statements define the individual changes that create the final database schema. This schema has to match the schema defined by the TABLE statement in the .hdbmigrationtable artifact. Please note that the compiler doesn't evaluate or process these SQL snippets. Any snippet is taken as is and inserted into the TABLE statement and the corresponding ALTER statement. The deployment fails in case of syntax errors.
CDS Model:
@cds.persistence.journal
@sql.append: 'PERSISTENT MEMORY ON'
entity E {
...,
@sql.append: 'FUZZY SEARCH INDEX ON'
text: String(100);
}
Result in hdbmigrationtable file:
== version=2
COLUMN TABLE E (
...,
text NVARCHAR(100) FUZZY SEARCH INDEX ON
) PERSISTENT MEMORY ON
== migration=2
ALTER TABLE E PERSISTENT MEMORY ON;
ALTER TABLE E ALTER (text NVARCHAR(100) FUZZY SEARCH INDEX ON);
It's important to understand that during deployment new migration versions will be applied on the existing database schema. If the resulting schema doesn't match the schema as defined by the TABLE statement, deployment fails and any changes are rolled-back. In consequence, when removing or replacing an existing @sql.append
annotation, the original ALTER statements need to be undone. As the required statements can't automatically be determined, manual resolution is required. The CDS build generates comments starting with >>>>
in order to provide some guidance and enforce manual resolution.
Generated file with comments:
== migration=3
>>>>> Manual resolution required - insert ALTER statement(s) as described below.
>>>>> After manual resolution delete all lines starting with >>>>>
>>>>> Insert ALTER statement for: annotation @sql.append of artifact E has been removed (previous value: "PERSISTENT MEMORY ON")
>>>>> Insert ALTER statement for: annotation @sql.append of element E:text has been removed (previous value: "FUZZY SEARCH INDEX ON")
Manually resolved file:
== migration=3
ALTER TABLE E PERSISTENT MEMORY DEFAULT;
ALTER TABLE E ALTER (text NVARCHAR(100) FUZZY SEARCH INDEX OFF);
Appending text to an existing annotation is possible without manual resolution. A valid ALTER statement will be generated in this case. For example, appending the NOT NULL
column constraint to an existing FUZZY SEARCH INDEX ON
annotation generates the following statement:
ALTER TABLE E ALTER (text NVARCHAR(100) FUZZY SEARCH INDEX ON NOT NULL);
WARNING
You can use @sql.append
to partition your table initially, but you can't subsequently change the partitions using schema evolution techniques as altering partitions isn't supported yet.
Advanced Options
The following CDS configuration options are supported to manage .hdbmigrationtable generation.
WARNING
This hasn't been finalized yet.
{
"hana" : {
"journal": {
"enable-drop": false,
"change-mode": "alter" // "drop"
},
// ...
}
}
The "enable-drop"
option determines whether incompatible model changes are rendered as is (true
) or manual resolution is required (false
). The default value is false
.
The change-mode
option determines whether ALTER TABLE ... ALTER
("alter"
) or ALTER TABLE ... DROP
("drop"
) statements are rendered for data type related changes. To ensure that any kind of model change can be successfully deployed to the database, you can switch the "change-mode"
to "drop"
, keeping in mind that any existing data will be deleted for the corresponding column. See hdbmigrationtable Generation for more details. The default value is "alter"
.
Caveats
CSV Data Gets Overridden
HDI deploys CSV data as .hdbtabledata and assumes exclusive ownership of the data. It's overridden with the next application deployment; hence:
TIP
Only use CSV files for configuration data that can't be changed by application users.
Yet, if you need to support initial data with user changes, you can use the include_filter
option that .hdbtabledata offers.
Undeploying Artifacts
As documented in the HDI Deployer docs, an HDI deployment by default never deletes artifacts. So, if you remove an entity or CSV files, the respective tables, and content remain in the database.
By default, cds add hana
creates an undeploy.json
like this:
[
"src/gen/**/*.hdbview",
"src/gen/**/*.hdbindex",
"src/gen/**/*.hdbconstraint",
"src/gen/**/*_drafts.hdbtable",
"src/gen/**/*.hdbcalculationview"
]
If you need to remove deployed CSV files, also add this entry:
[
[...]
"src/gen/**/*.hdbtabledata"
]
See this troubleshooting entry for more information.
SAP HANA Cloud System Limits
All limitations for the SAP HANA Cloud database can be found in the SAP Help Portal.
Native Associations
For SAP HANA, CDS associations are by default reflected in the respective database tables and views by Native HANA Associations (HANA SQL clause WITH ASSOCIATIONS
).
CAP no longer needs these native associations (provided you use the new database service @cap-js/hana for the CAP Node.js stack).
Unless you explicitly use them in other native HANA objects, we recommend switching off the generation of native HANA associations, as they increase deploy times: They need to be validated in the HDI deployment, and they can introduce indirect dependencies between other objects, which can trigger other unnecessary revalidations or even unnecessary drop/create of indexes. By switching them off, all this effort is saved.
{
"cds": {
"sql": {
"native_hana_associations": false
}
}
}
{
"sql": {
"native_hana_associations": false
}
}
For new projects, cds add hana
automatically adds this configuration.
Note that the first deployment after this configuration change may take longer, as for each entity with associations the respective database object will be touched (DROP/CREATE for views, full table migration via shadow table and data copy for tables). This is also the reason why we haven't changed the default so far. Subsequent deployments will benefit, however.