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feat(sap): add support for REAL_VECTOR and HALF_VECTOR data types in SAP HANA Cloud (#11526)
* feat(sap): add support for REAL_VECTOR data type * feat(sap): add support for HALF_VECTOR data type
This commit is contained in:
Lucian Mocanu
GitHub
parent
f2d2236218
commit
abf8863a53
@ -401,9 +401,14 @@ or
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### Column types for `sap`
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`tinyint`, `smallint`, `integer`, `bigint`, `smalldecimal`, `decimal`, `real`, `double`, `date`, `time`, `seconddate`, `timestamp`, `boolean`, `char`, `nchar`, `varchar`, `nvarchar`, `text`, `alphanum`, `shorttext`, `array`, `varbinary`, `blob`, `clob`, `nclob`, `st_geometry`, `st_point`.
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SAP HANA 2.0 and SAP HANA Cloud support slightly different data types. Check the SAP Help pages for more information:
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> Note: SAP HANA Cloud deprecated or removed some of these data types. TypeORM will convert them to the closest available alternative when connected to a Cloud version.
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- [SAP HANA 2.0 Data Types](https://help.sap.com/docs/SAP_HANA_PLATFORM/4fe29514fd584807ac9f2a04f6754767/20a1569875191014b507cf392724b7eb.html?locale=en-US)
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- [SAP HANA Cloud Data Types](https://help.sap.com/docs/hana-cloud-database/sap-hana-cloud-sap-hana-database-sql-reference-guide/data-types)
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TypeORM's `SapDriver` supports `tinyint`, `smallint`, `integer`, `bigint`, `smalldecimal`, `decimal`, `real`, `double`, `date`, `time`, `seconddate`, `timestamp`, `boolean`, `char`, `nchar`, `varchar`, `nvarchar`, `text`, `alphanum`, `shorttext`, `array`, `varbinary`, `blob`, `clob`, `nclob`, `st_geometry`, `st_point`, `real_vector` and `half_vector`. Some of these data types have been deprecated or removed in SAP HANA Cloud, and will be converted to the closest available alternative when connected to a Cloud database.
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The `real_vector` and `half_vector` data types were introduced in SAP HANA Cloud (2024Q1 and 2025Q2 respectively), and require a supported version of `@sap/hana-client` as well. By default, the client will return a `Buffer` in the `fvecs`/`hvecs` format, which is more efficient. It is possible to let the driver convert the values to a `number[]` by adding `{ extra: { vectorOutputType: "Array" } }` to the connection options. Check the SAP HANA Client documentation for more information about [REAL_VECTOR](https://help.sap.com/docs/SAP_HANA_CLIENT/f1b440ded6144a54ada97ff95dac7adf/0d197e4389c64e6b9cf90f6f698f62fe.html) or [HALF_VECTOR](https://help.sap.com/docs/SAP_HANA_CLIENT/f1b440ded6144a54ada97ff95dac7adf/8bb854b4ce4a4299bed27c365b717e91.html).
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### Column types for `spanner`
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8
package-lock.json
generated
8
package-lock.json
generated
@ -31,7 +31,7 @@
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},
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"devDependencies": {
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"@eslint/js": "^9.28.0",
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"@sap/hana-client": "^2.24.21",
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"@sap/hana-client": "^2.25.22",
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"@tsconfig/node16": "^16.1.4",
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"@types/chai": "^4.3.20",
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"@types/chai-as-promised": "^7.1.8",
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@ -2491,9 +2491,9 @@
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}
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},
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"node_modules/@sap/hana-client": {
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"version": "2.24.21",
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"resolved": "https://registry.npmjs.org/@sap/hana-client/-/hana-client-2.24.21.tgz",
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"integrity": "sha512-Mat/LwhvboZqbBKXxLDJz+Xtjf+Hht/SDaVRmzCoNDrbWNKiWIGZ5b9xQVBAXZFfU6GTzFQPcP1wGLBb71BRRg==",
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"version": "2.25.22",
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"resolved": "https://registry.npmjs.org/@sap/hana-client/-/hana-client-2.25.22.tgz",
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"integrity": "sha512-85JtWAEM3HXsXl6/9+Ppmm7aQ8QmHQTzBJsHTv8hn4Ju4WkLcrjQtSHR0qYe8hiA5PMYd2RGtgGCoAjLi63+5g==",
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"dev": true,
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"hasInstallScript": true,
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"hasShrinkwrap": true,
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@ -109,7 +109,7 @@
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},
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"devDependencies": {
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"@eslint/js": "^9.28.0",
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"@sap/hana-client": "^2.24.21",
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"@sap/hana-client": "^2.25.22",
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"@tsconfig/node16": "^16.1.4",
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"@types/chai": "^4.3.20",
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"@types/chai-as-promised": "^7.1.8",
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@ -109,36 +109,39 @@ export class SapDriver implements Driver {
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* @see https://help.sap.com/docs/hana-cloud-database/sap-hana-cloud-sap-hana-database-sql-reference-guide/data-types
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*/
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supportedDataTypes: ColumnType[] = [
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"tinyint",
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"smallint",
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"int", // typeorm alias for "integer"
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"integer",
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"alphanum", // removed in SAP HANA Cloud
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"array",
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"bigint",
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"smalldecimal",
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"decimal",
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"dec", // typeorm alias for "decimal"
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"real",
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"double",
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"float", // database alias for "real" / "double"
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"date",
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"time",
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"seconddate",
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"timestamp",
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"binary",
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"blob",
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"boolean",
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"char", // not officially supported, in SAP HANA Cloud: alias for "nchar"
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"nchar", // not officially supported
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"varchar", // in SAP HANA Cloud: alias for "nvarchar"
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"nvarchar",
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"text", // removed in SAP HANA Cloud
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"alphanum", // removed in SAP HANA Cloud
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"shorttext", // removed in SAP HANA Cloud
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"array",
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"varbinary",
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"blob",
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"clob", // in SAP HANA Cloud: alias for "nclob"
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"date",
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"dec", // typeorm alias for "decimal"
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"decimal",
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"double",
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"float", // database alias for "real" / "double"
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"half_vector", // only supported in SAP HANA Cloud, not in SAP HANA 2.0
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"int", // typeorm alias for "integer"
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"integer",
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"nchar", // not officially supported
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"nclob",
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"nvarchar",
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"real_vector", // only supported in SAP HANA Cloud, not in SAP HANA 2.0
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"real",
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"seconddate",
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"shorttext", // removed in SAP HANA Cloud
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"smalldecimal",
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"smallint",
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"st_geometry",
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"st_point",
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"text", // removed in SAP HANA Cloud
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"time",
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"timestamp",
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"tinyint",
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"varbinary",
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"varchar", // in SAP HANA Cloud: alias for "nvarchar"
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]
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/**
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@ -155,11 +158,14 @@ export class SapDriver implements Driver {
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* Gets list of column data types that support length by a driver.
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*/
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withLengthColumnTypes: ColumnType[] = [
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"varchar",
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"nvarchar",
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"alphanum",
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"binary",
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"half_vector",
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"nvarchar",
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"real_vector",
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"shorttext",
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"varbinary",
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"varchar",
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]
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/**
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@ -170,7 +176,7 @@ export class SapDriver implements Driver {
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/**
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* Gets list of column data types that support scale by a driver.
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*/
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withScaleColumnTypes: ColumnType[] = ["decimal"]
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withScaleColumnTypes: ColumnType[] = ["decimal", "timestamp"]
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/**
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* Orm has special columns and we need to know what database column types should be for those types.
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@ -207,13 +213,14 @@ export class SapDriver implements Driver {
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* Used in the cases when length/precision/scale is not specified by user.
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*/
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dataTypeDefaults: DataTypeDefaults = {
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binary: { length: 1 },
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char: { length: 1 },
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decimal: { precision: 18, scale: 0 },
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nchar: { length: 1 },
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varchar: { length: 255 },
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nvarchar: { length: 255 },
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shorttext: { length: 255 },
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varbinary: { length: 255 },
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decimal: { precision: 18, scale: 0 },
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varchar: { length: 255 },
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}
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/**
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@ -493,9 +500,7 @@ export class SapDriver implements Driver {
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if (value === null || value === undefined) return value
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if (columnMetadata.type === Boolean) {
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return value === true ? 1 : 0
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} else if (columnMetadata.type === "date") {
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if (columnMetadata.type === "date") {
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return DateUtils.mixedDateToDateString(value)
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} else if (columnMetadata.type === "time") {
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return DateUtils.mixedDateToTimeString(value)
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@ -531,9 +536,7 @@ export class SapDriver implements Driver {
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)
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: value
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if (columnMetadata.type === Boolean) {
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value = value ? true : false
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} else if (
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if (
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columnMetadata.type === "timestamp" ||
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columnMetadata.type === "seconddate" ||
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columnMetadata.type === Date
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@ -549,9 +552,6 @@ export class SapDriver implements Driver {
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value = DateUtils.stringToSimpleJson(value)
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} else if (columnMetadata.type === "simple-enum") {
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value = DateUtils.stringToSimpleEnum(value, columnMetadata)
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} else if (columnMetadata.type === Number) {
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// convert to number if number
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value = !isNaN(+value) ? parseInt(value) : value
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}
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if (columnMetadata.transformer)
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@ -620,6 +620,13 @@ export class SapDriver implements Driver {
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} else if (column.type === "char") {
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return "nchar"
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}
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} else {
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if (
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column.type === "real_vector" ||
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column.type === "half_vector"
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) {
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return "varbinary"
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}
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}
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return (column.type as string) || ""
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@ -47,7 +47,7 @@ export type WithPrecisionColumnType =
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| "time" // mysql, postgres, mssql, cockroachdb
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| "time with time zone" // postgres, cockroachdb
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| "time without time zone" // postgres
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| "timestamp" // mysql, postgres, mssql, oracle, cockroachdb, spanner
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| "timestamp" // mysql, postgres, mssql, oracle, cockroachdb, sap, spanner
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| "timestamp without time zone" // postgres, cockroachdb
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| "timestamp with time zone" // postgres, oracle, cockroachdb
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| "timestamp with local time zone" // oracle
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@ -75,6 +75,8 @@ export type WithLengthColumnType =
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| "binary" // mssql
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| "varbinary" // mssql, sap
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| "string" // cockroachdb, spanner
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| "half_vector" // sap
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| "real_vector" // sap
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export type WithWidthColumnType =
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| "tinyint" // mysql
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@ -129,10 +129,7 @@ export class EntityMetadataValidator {
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const normalizedColumn = driver.normalizeType(
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column,
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) as ColumnType
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if (
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driver.supportedDataTypes.indexOf(normalizedColumn) ===
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-1
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)
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if (!driver.supportedDataTypes.includes(normalizedColumn))
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throw new DataTypeNotSupportedError(
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column,
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normalizedColumn,
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@ -140,9 +137,7 @@ export class EntityMetadataValidator {
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)
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if (
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column.length &&
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driver.withLengthColumnTypes.indexOf(
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normalizedColumn,
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) === -1
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!driver.withLengthColumnTypes.includes(normalizedColumn)
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)
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throw new TypeORMError(
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`Column ${column.propertyName} of Entity ${entityMetadata.name} does not support length property.`,
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@ -316,8 +311,6 @@ export class EntityMetadataValidator {
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`This may lead to unexpected circular removals. Please set cascade remove only from one side of relationship.`,
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)
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}) // todo: maybe better just deny removal from one to one relation without join column?
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entityMetadata.eagerRelations.forEach((relation) => {})
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}
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/**
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@ -1,8 +1,8 @@
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import "reflect-metadata"
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import { DataSource } from "../../../../../src"
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import { expect } from "chai"
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import { DataSource, DeepPartial } from "../../../../../src"
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import { DriverUtils } from "../../../../../src/driver/DriverUtils"
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import { DateUtils } from "../../../../../src/util/DateUtils"
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import {
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closeTestingConnections,
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createTestingConnections,
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@ -13,347 +13,290 @@ import { PostWithOptions } from "./entity/PostWithOptions"
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import { PostWithoutTypes } from "./entity/PostWithoutTypes"
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describe("database schema > column types > sap", () => {
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let connections: DataSource[]
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let dataSources: DataSource[]
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before(async () => {
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connections = await createTestingConnections({
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dataSources = await createTestingConnections({
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entities: [__dirname + "/entity/*{.js,.ts}"],
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enabledDrivers: ["sap"],
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})
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})
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beforeEach(() => reloadTestingDatabases(connections))
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after(() => closeTestingConnections(connections))
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beforeEach(() => reloadTestingDatabases(dataSources))
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after(() => closeTestingConnections(dataSources))
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it("all types should work correctly - persist and hydrate", () =>
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Promise.all(
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connections.map(async (connection) => {
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// this test contains data types that are available only in SAP HANA 2.0 and that have been removed in SAP HANA Cloud
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const postRepository = connection.getRepository(Post)
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const queryRunner = connection.createQueryRunner()
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const table = await queryRunner.getTable("post")
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await queryRunner.release()
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dataSources.map(async (dataSource) => {
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const plainPost = {
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id: 1,
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name: "Post",
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int: 2147483647,
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integer: 2147483647,
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tinyint: 250,
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smallint: 32767,
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bigint: "8223372036854775807",
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decimal: "8223372036854775807",
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dec: "8223372036854775807",
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smalldecimal: "8223372036854775",
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real: 10.5,
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double: 10.53,
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float: 10.53,
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char: "A",
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nchar: "A",
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varchar: "This is varchar",
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nvarchar: "This is nvarchar",
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alphanum: "This is alphanum",
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text: "This is text",
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shorttext: "This is shorttext",
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date: "2017-06-21",
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time: "13:27:05",
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timestamp: new Date(),
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seconddate: (() => {
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const d = new Date()
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d.setMilliseconds(0)
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return d
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})(),
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blob: Buffer.from("This is blob"),
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clob: "This is clob",
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nclob: "This is nclob",
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boolean: true,
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// array: ["A", "B", "C"]; // TODO
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varbinary: Buffer.from("This is varbinary"),
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simpleArray: ["A", "B", "C"],
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} satisfies DeepPartial<Post>
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const post = new Post()
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post.id = 1
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post.name = "Post"
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post.int = 2147483647
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post.integer = 2147483647
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post.tinyint = 250
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post.smallint = 32767
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post.bigint = "8223372036854775807"
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post.decimal = "8223372036854775807"
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post.dec = "8223372036854775807"
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post.smalldecimal = "8223372036854775"
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post.real = 10.5
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post.double = 10.53
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post.float = 10.53
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post.char = "A"
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post.nchar = "A"
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post.varchar = "This is varchar"
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post.nvarchar = "This is nvarchar"
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post.alphanum = "This is alphanum"
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post.text = "This is text"
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post.shorttext = "This is shorttext"
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post.dateObj = new Date()
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post.date = "2017-06-21"
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post.timeObj = new Date()
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post.time = "13:27:05"
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post.timestamp = new Date()
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post.timestamp.setMilliseconds(0)
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post.seconddate = new Date()
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post.seconddate.setMilliseconds(0)
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post.blob = Buffer.from("This is blob")
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post.clob = "This is clob"
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post.nclob = "This is nclob"
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post.boolean = true
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// post.array = ["A", "B", "C"]; // TODO
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post.varbinary = Buffer.from("This is varbinary")
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post.simpleArray = ["A", "B", "C"]
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const postRepository = dataSource.getRepository(Post)
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const post = postRepository.create(plainPost)
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await postRepository.save(post)
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const loadedPost = (await postRepository.findOneBy({
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const loadedPost = await postRepository.findOneBy({
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id: 1,
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}))!
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loadedPost.id.should.be.equal(post.id)
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loadedPost.name.should.be.equal(post.name)
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loadedPost.int.should.be.equal(post.int)
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loadedPost.integer.should.be.equal(post.integer)
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loadedPost.tinyint.should.be.equal(post.tinyint)
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loadedPost.smallint.should.be.equal(post.smallint)
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loadedPost.bigint.should.be.equal(post.bigint)
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loadedPost.decimal.should.be.equal(post.decimal)
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loadedPost.dec.should.be.equal(post.dec)
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loadedPost.smalldecimal.should.be.equal(post.smalldecimal)
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loadedPost.real.should.be.equal(post.real)
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loadedPost.double.should.be.equal(post.double)
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loadedPost.float.should.be.equal(post.float)
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loadedPost.char.should.be.equal(post.char)
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loadedPost.nchar.should.be.equal(post.nchar)
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loadedPost.varchar.should.be.equal(post.varchar)
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loadedPost.nvarchar.should.be.equal(post.nvarchar)
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loadedPost.alphanum.should.be.equal(post.alphanum)
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loadedPost.text.should.be.equal(post.text)
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loadedPost.shorttext.should.be.equal(post.shorttext)
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loadedPost.dateObj.should.be.equal(
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DateUtils.mixedDateToDateString(post.dateObj),
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)
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loadedPost.date.should.be.equal(post.date)
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loadedPost.timeObj
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.valueOf()
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.should.be.equal(DateUtils.mixedTimeToString(post.timeObj))
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loadedPost.time.should.be.equal(post.time)
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loadedPost.timestamp
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.valueOf()
|
||||
.should.be.equal(post.timestamp.valueOf())
|
||||
loadedPost.seconddate
|
||||
.valueOf()
|
||||
.should.be.equal(post.seconddate.valueOf())
|
||||
loadedPost.blob.toString().should.be.equal(post.blob.toString())
|
||||
loadedPost.clob.toString().should.be.equal(post.clob.toString())
|
||||
loadedPost.nclob
|
||||
.toString()
|
||||
.should.be.equal(post.nclob.toString())
|
||||
loadedPost.boolean.should.be.equal(post.boolean)
|
||||
loadedPost.varbinary
|
||||
.toString()
|
||||
.should.be.equal(post.varbinary.toString())
|
||||
loadedPost.simpleArray[0].should.be.equal(post.simpleArray[0])
|
||||
loadedPost.simpleArray[1].should.be.equal(post.simpleArray[1])
|
||||
loadedPost.simpleArray[2].should.be.equal(post.simpleArray[2])
|
||||
})
|
||||
expect(loadedPost).to.deep.equal({
|
||||
...plainPost,
|
||||
})
|
||||
|
||||
table!.findColumnByName("id")!.type.should.be.equal("integer")
|
||||
table!
|
||||
.findColumnByName("name")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!.findColumnByName("int")!.type.should.be.equal("integer")
|
||||
table!
|
||||
.findColumnByName("integer")!
|
||||
.type.should.be.equal("integer")
|
||||
table!
|
||||
.findColumnByName("tinyint")!
|
||||
.type.should.be.equal("tinyint")
|
||||
table!
|
||||
.findColumnByName("smallint")!
|
||||
.type.should.be.equal("smallint")
|
||||
table!
|
||||
.findColumnByName("bigint")!
|
||||
.type.should.be.equal("bigint")
|
||||
table!
|
||||
.findColumnByName("decimal")!
|
||||
.type.should.be.equal("decimal")
|
||||
table!.findColumnByName("dec")!.type.should.be.equal("decimal")
|
||||
table!.findColumnByName("real")!.type.should.be.equal("real")
|
||||
table!
|
||||
.findColumnByName("double")!
|
||||
.type.should.be.equal("double")
|
||||
table!.findColumnByName("float")!.type.should.be.equal("double")
|
||||
table!.findColumnByName("nchar")!.type.should.be.equal("nchar")
|
||||
table!
|
||||
.findColumnByName("nvarchar")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!.findColumnByName("dateObj")!.type.should.be.equal("date")
|
||||
table!.findColumnByName("date")!.type.should.be.equal("date")
|
||||
table!.findColumnByName("timeObj")!.type.should.be.equal("time")
|
||||
table!.findColumnByName("time")!.type.should.be.equal("time")
|
||||
table!
|
||||
.findColumnByName("timestamp")!
|
||||
.type.should.be.equal("timestamp")
|
||||
table!
|
||||
.findColumnByName("seconddate")!
|
||||
.type.should.be.equal("seconddate")
|
||||
table!.findColumnByName("blob")!.type.should.be.equal("blob")
|
||||
table!.findColumnByName("nclob")!.type.should.be.equal("nclob")
|
||||
table!
|
||||
.findColumnByName("boolean")!
|
||||
.type.should.be.equal("boolean")
|
||||
table!
|
||||
.findColumnByName("varbinary")!
|
||||
.type.should.be.equal("varbinary")
|
||||
table!
|
||||
.findColumnByName("simpleArray")!
|
||||
.type.should.be.equal("nclob")
|
||||
// Verify column metadata
|
||||
const queryRunner = dataSource.createQueryRunner()
|
||||
const table = (await queryRunner.getTable(
|
||||
dataSource.getMetadata(Post).tableName,
|
||||
))!
|
||||
await queryRunner.release()
|
||||
expect(table.findColumnByName("id")!.type).to.equal("integer")
|
||||
expect(table.findColumnByName("name")!.type).to.equal(
|
||||
"nvarchar",
|
||||
)
|
||||
expect(table.findColumnByName("int")!.type).to.equal("integer")
|
||||
expect(table.findColumnByName("integer")!.type).to.equal(
|
||||
"integer",
|
||||
)
|
||||
expect(table.findColumnByName("tinyint")!.type).to.equal(
|
||||
"tinyint",
|
||||
)
|
||||
expect(table.findColumnByName("smallint")!.type).to.equal(
|
||||
"smallint",
|
||||
)
|
||||
expect(table.findColumnByName("bigint")!.type).to.equal(
|
||||
"bigint",
|
||||
)
|
||||
expect(table.findColumnByName("decimal")!.type).to.equal(
|
||||
"decimal",
|
||||
)
|
||||
expect(table.findColumnByName("dec")!.type).to.equal("decimal")
|
||||
expect(table.findColumnByName("real")!.type).to.equal("real")
|
||||
expect(table.findColumnByName("double")!.type).to.equal(
|
||||
"double",
|
||||
)
|
||||
expect(table.findColumnByName("float")!.type).to.equal("double")
|
||||
expect(table.findColumnByName("nchar")!.type).to.equal("nchar")
|
||||
expect(table.findColumnByName("nvarchar")!.type).to.equal(
|
||||
"nvarchar",
|
||||
)
|
||||
expect(table.findColumnByName("date")!.type).to.equal("date")
|
||||
expect(table.findColumnByName("time")!.type).to.equal("time")
|
||||
expect(table.findColumnByName("timestamp")!.type).to.equal(
|
||||
"timestamp",
|
||||
)
|
||||
expect(table.findColumnByName("seconddate")!.type).to.equal(
|
||||
"seconddate",
|
||||
)
|
||||
expect(table.findColumnByName("blob")!.type).to.equal("blob")
|
||||
expect(table.findColumnByName("nclob")!.type).to.equal("nclob")
|
||||
expect(table.findColumnByName("boolean")!.type).to.equal(
|
||||
"boolean",
|
||||
)
|
||||
expect(table.findColumnByName("varbinary")!.type).to.equal(
|
||||
"varbinary",
|
||||
)
|
||||
expect(table.findColumnByName("simpleArray")!.type).to.equal(
|
||||
"nclob",
|
||||
)
|
||||
|
||||
// Deprecated column types that have a different behavior in SAP HANA Cloud
|
||||
if (
|
||||
DriverUtils.isReleaseVersionOrGreater(
|
||||
connection.driver,
|
||||
dataSource.driver,
|
||||
"4.0",
|
||||
)
|
||||
) {
|
||||
table!
|
||||
.findColumnByName("char")!
|
||||
.type.should.be.equal("nchar")
|
||||
table!
|
||||
.findColumnByName("varchar")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("alphanum")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("shorttext")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("text")!
|
||||
.type.should.be.equal("nclob")
|
||||
table!
|
||||
.findColumnByName("clob")!
|
||||
.type.should.be.equal("nclob")
|
||||
expect(table.findColumnByName("char")!.type).to.equal(
|
||||
"nchar",
|
||||
)
|
||||
expect(table.findColumnByName("varchar")!.type).to.equal(
|
||||
"nvarchar",
|
||||
)
|
||||
expect(table.findColumnByName("alphanum")!.type).to.equal(
|
||||
"nvarchar",
|
||||
)
|
||||
expect(table.findColumnByName("shorttext")!.type).to.equal(
|
||||
"nvarchar",
|
||||
)
|
||||
expect(table.findColumnByName("text")!.type).to.equal(
|
||||
"nclob",
|
||||
)
|
||||
expect(table.findColumnByName("clob")!.type).to.equal(
|
||||
"nclob",
|
||||
)
|
||||
} else {
|
||||
table!
|
||||
.findColumnByName("char")!
|
||||
.type.should.be.equal("char")
|
||||
table!
|
||||
.findColumnByName("varchar")!
|
||||
.type.should.be.equal("varchar")
|
||||
table!
|
||||
.findColumnByName("alphanum")!
|
||||
.type.should.be.equal("alphanum")
|
||||
table!
|
||||
.findColumnByName("shorttext")!
|
||||
.type.should.be.equal("shorttext")
|
||||
table!
|
||||
.findColumnByName("text")!
|
||||
.type.should.be.equal("text")
|
||||
table!
|
||||
.findColumnByName("clob")!
|
||||
.type.should.be.equal("clob")
|
||||
expect(table.findColumnByName("char")!.type).to.equal(
|
||||
"char",
|
||||
)
|
||||
expect(table.findColumnByName("varchar")!.type).to.equal(
|
||||
"varchar",
|
||||
)
|
||||
expect(table.findColumnByName("alphanum")!.type).to.equal(
|
||||
"alphanum",
|
||||
)
|
||||
expect(table.findColumnByName("shorttext")!.type).to.equal(
|
||||
"shorttext",
|
||||
)
|
||||
expect(table.findColumnByName("text")!.type).to.equal(
|
||||
"text",
|
||||
)
|
||||
expect(table.findColumnByName("clob")!.type).to.equal(
|
||||
"clob",
|
||||
)
|
||||
}
|
||||
}),
|
||||
))
|
||||
|
||||
it("all types should work correctly - persist and hydrate when options are specified on columns", () =>
|
||||
Promise.all(
|
||||
connections.map(async (connection) => {
|
||||
const postRepository = connection.getRepository(PostWithOptions)
|
||||
const queryRunner = connection.createQueryRunner()
|
||||
const table = await queryRunner.getTable("post_with_options")
|
||||
await queryRunner.release()
|
||||
dataSources.map(async (dataSource) => {
|
||||
const plainPost = {
|
||||
id: 1,
|
||||
dec: "60.00",
|
||||
decimal: "70.000",
|
||||
varchar: "This is varchar",
|
||||
nvarchar: "This is nvarchar",
|
||||
alphanum: "This is alphanum",
|
||||
shorttext: "This is shorttext",
|
||||
} satisfies DeepPartial<PostWithOptions>
|
||||
|
||||
const post = new PostWithOptions()
|
||||
post.id = 1
|
||||
post.dec = "60.00"
|
||||
post.decimal = "70.000"
|
||||
post.varchar = "This is varchar"
|
||||
post.nvarchar = "This is nvarchar"
|
||||
post.alphanum = "This is alphanum"
|
||||
post.shorttext = "This is shorttext"
|
||||
const postRepository = dataSource.getRepository(PostWithOptions)
|
||||
const post = postRepository.create(plainPost)
|
||||
await postRepository.save(post)
|
||||
|
||||
const loadedPost = (await postRepository.findOneBy({
|
||||
const loadedPost = await postRepository.findOneBy({
|
||||
id: 1,
|
||||
}))!
|
||||
loadedPost.id.should.be.equal(post.id)
|
||||
loadedPost.dec.should.be.equal(post.dec)
|
||||
loadedPost.decimal.should.be.equal(post.decimal)
|
||||
loadedPost.varchar.should.be.equal(post.varchar)
|
||||
loadedPost.nvarchar.should.be.equal(post.nvarchar)
|
||||
loadedPost.alphanum.should.be.equal(post.alphanum)
|
||||
loadedPost.shorttext.should.be.equal(post.shorttext)
|
||||
})
|
||||
expect(loadedPost).to.deep.equal(plainPost)
|
||||
|
||||
table!.findColumnByName("id")!.type.should.be.equal("integer")
|
||||
table!.findColumnByName("dec")!.type.should.be.equal("decimal")
|
||||
table!.findColumnByName("dec")!.precision!.should.be.equal(10)
|
||||
table!.findColumnByName("dec")!.scale!.should.be.equal(2)
|
||||
table!
|
||||
.findColumnByName("decimal")!
|
||||
.type.should.be.equal("decimal")
|
||||
table!
|
||||
.findColumnByName("decimal")!
|
||||
.precision!.should.be.equal(10)
|
||||
table!.findColumnByName("decimal")!.scale!.should.be.equal(3)
|
||||
table!
|
||||
.findColumnByName("nvarchar")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("nvarchar")!
|
||||
.length!.should.be.equal("50")
|
||||
// Verify column metadata
|
||||
const queryRunner = dataSource.createQueryRunner()
|
||||
const table = (await queryRunner.getTable(
|
||||
dataSource.getMetadata(PostWithOptions).tableName,
|
||||
))!
|
||||
await queryRunner.release()
|
||||
expect(table.findColumnByName("id")!.type).to.equal("integer")
|
||||
expect(table.findColumnByName("dec")).to.include({
|
||||
type: "decimal",
|
||||
precision: 10,
|
||||
scale: 2,
|
||||
})
|
||||
expect(table.findColumnByName("decimal")).to.include({
|
||||
type: "decimal",
|
||||
precision: 10,
|
||||
scale: 3,
|
||||
})
|
||||
expect(table.findColumnByName("nvarchar")).to.include({
|
||||
type: "nvarchar",
|
||||
length: "50",
|
||||
})
|
||||
|
||||
// Deprecated column types that have a different behavior in SAP HANA Cloud
|
||||
if (
|
||||
DriverUtils.isReleaseVersionOrGreater(
|
||||
connection.driver,
|
||||
dataSource.driver,
|
||||
"4.0",
|
||||
)
|
||||
) {
|
||||
table!
|
||||
.findColumnByName("varchar")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("varchar")!
|
||||
.length!.should.be.equal("50")
|
||||
table!
|
||||
.findColumnByName("alphanum")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("alphanum")!
|
||||
.length!.should.be.equal("50")
|
||||
table!
|
||||
.findColumnByName("shorttext")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("shorttext")!
|
||||
.length!.should.be.equal("50")
|
||||
expect(table.findColumnByName("varchar")).to.include({
|
||||
type: "nvarchar",
|
||||
length: "50",
|
||||
})
|
||||
expect(table.findColumnByName("alphanum")).to.include({
|
||||
type: "nvarchar",
|
||||
length: "50",
|
||||
})
|
||||
expect(table.findColumnByName("shorttext")).to.include({
|
||||
type: "nvarchar",
|
||||
length: "50",
|
||||
})
|
||||
} else {
|
||||
table!
|
||||
.findColumnByName("varchar")!
|
||||
.type.should.be.equal("varchar")
|
||||
table!
|
||||
.findColumnByName("varchar")!
|
||||
.length!.should.be.equal("50")
|
||||
table!
|
||||
.findColumnByName("alphanum")!
|
||||
.type.should.be.equal("alphanum")
|
||||
table!
|
||||
.findColumnByName("alphanum")!
|
||||
.length!.should.be.equal("50")
|
||||
table!
|
||||
.findColumnByName("shorttext")!
|
||||
.type.should.be.equal("shorttext")
|
||||
table!
|
||||
.findColumnByName("shorttext")!
|
||||
.length!.should.be.equal("50")
|
||||
expect(table.findColumnByName("varchar")).to.include({
|
||||
type: "varchar",
|
||||
length: "50",
|
||||
})
|
||||
expect(table.findColumnByName("alphanum")).to.include({
|
||||
type: "alphanum",
|
||||
length: "50",
|
||||
})
|
||||
expect(table.findColumnByName("shorttext")).to.include({
|
||||
type: "shorttext",
|
||||
length: "50",
|
||||
})
|
||||
}
|
||||
}),
|
||||
))
|
||||
|
||||
it("all types should work correctly - persist and hydrate when types are not specified on columns", () =>
|
||||
Promise.all(
|
||||
connections.map(async (connection) => {
|
||||
const postRepository =
|
||||
connection.getRepository(PostWithoutTypes)
|
||||
const queryRunner = connection.createQueryRunner()
|
||||
const table = await queryRunner.getTable("post_without_types")
|
||||
await queryRunner.release()
|
||||
dataSources.map(async (dataSource) => {
|
||||
const plainPost = {
|
||||
id: 1,
|
||||
name: "Post",
|
||||
boolean: true,
|
||||
blob: Buffer.from("This is blob"),
|
||||
timestamp: new Date(),
|
||||
} satisfies DeepPartial<PostWithoutTypes>
|
||||
|
||||
const post = new PostWithoutTypes()
|
||||
post.id = 1
|
||||
post.name = "Post"
|
||||
post.boolean = true
|
||||
post.blob = Buffer.from("This is blob")
|
||||
post.timestamp = new Date()
|
||||
const postRepository =
|
||||
dataSource.getRepository(PostWithoutTypes)
|
||||
const post = postRepository.create(plainPost)
|
||||
await postRepository.save(post)
|
||||
|
||||
const loadedPost = (await postRepository.findOneBy({
|
||||
const loadedPost = await postRepository.findOneBy({
|
||||
id: 1,
|
||||
}))!
|
||||
loadedPost.id.should.be.equal(post.id)
|
||||
loadedPost.name.should.be.equal(post.name)
|
||||
loadedPost.boolean.should.be.equal(post.boolean)
|
||||
loadedPost.blob.toString().should.be.equal(post.blob.toString())
|
||||
loadedPost.timestamp
|
||||
.valueOf()
|
||||
.should.be.equal(post.timestamp.valueOf())
|
||||
})
|
||||
expect(loadedPost).to.deep.equal(plainPost)
|
||||
|
||||
table!.findColumnByName("id")!.type.should.be.equal("integer")
|
||||
table!
|
||||
.findColumnByName("name")!
|
||||
.type.should.be.equal("nvarchar")
|
||||
table!
|
||||
.findColumnByName("boolean")!
|
||||
.type.should.be.equal("boolean")
|
||||
table!.findColumnByName("blob")!.type.should.be.equal("blob")
|
||||
table!
|
||||
.findColumnByName("timestamp")!
|
||||
.type.should.be.equal("timestamp")
|
||||
// Verify column metadata
|
||||
const queryRunner = dataSource.createQueryRunner()
|
||||
const table = (await queryRunner.getTable(
|
||||
dataSource.getMetadata(PostWithoutTypes).tableName,
|
||||
))!
|
||||
await queryRunner.release()
|
||||
expect(table.findColumnByName("id")!.type).to.equal("integer")
|
||||
expect(table.findColumnByName("name")!.type).to.equal(
|
||||
"nvarchar",
|
||||
)
|
||||
expect(table.findColumnByName("boolean")!.type).to.equal(
|
||||
"boolean",
|
||||
)
|
||||
expect(table.findColumnByName("blob")!.type).to.equal("blob")
|
||||
expect(table.findColumnByName("timestamp")!.type).to.equal(
|
||||
"timestamp",
|
||||
)
|
||||
}),
|
||||
))
|
||||
})
|
||||
|
||||
@ -1,6 +1,4 @@
|
||||
import { Entity } from "../../../../../../src"
|
||||
import { PrimaryColumn } from "../../../../../../src"
|
||||
import { Column } from "../../../../../../src"
|
||||
import { Column, Entity, PrimaryColumn } from "../../../../../../src"
|
||||
|
||||
@Entity()
|
||||
export class Post {
|
||||
@ -76,15 +74,9 @@ export class Post {
|
||||
// Date Types
|
||||
// -------------------------------------------------------------------------
|
||||
|
||||
@Column("date")
|
||||
dateObj: Date
|
||||
|
||||
@Column("date")
|
||||
date: string
|
||||
|
||||
@Column("time")
|
||||
timeObj: Date
|
||||
|
||||
@Column("time")
|
||||
time: string
|
||||
|
||||
|
||||
@ -1,6 +1,4 @@
|
||||
import { Entity } from "../../../../../../src"
|
||||
import { PrimaryColumn } from "../../../../../../src"
|
||||
import { Column } from "../../../../../../src"
|
||||
import { Column, Entity, PrimaryColumn } from "../../../../../../src"
|
||||
|
||||
@Entity()
|
||||
export class PostWithOptions {
|
||||
|
||||
@ -1,6 +1,4 @@
|
||||
import { Entity } from "../../../../../../src"
|
||||
import { PrimaryColumn } from "../../../../../../src"
|
||||
import { Column } from "../../../../../../src"
|
||||
import { Column, Entity, PrimaryColumn } from "../../../../../../src"
|
||||
|
||||
@Entity()
|
||||
export class PostWithoutTypes {
|
||||
|
||||
@ -0,0 +1,27 @@
|
||||
import { Column, Entity, PrimaryColumn } from "../../../../../../src"
|
||||
|
||||
@Entity()
|
||||
export class ArrayEmbedding {
|
||||
@PrimaryColumn()
|
||||
id: number
|
||||
|
||||
@Column("nclob")
|
||||
content: string
|
||||
|
||||
@Column("nclob")
|
||||
metadata: string
|
||||
|
||||
@Column("real_vector", {
|
||||
length: 16,
|
||||
})
|
||||
smallVector: number[]
|
||||
|
||||
@Column("real_vector", {
|
||||
length: 1536,
|
||||
nullable: true,
|
||||
})
|
||||
largeVector: number[] | null
|
||||
|
||||
@Column("real_vector")
|
||||
variableVector: number[]
|
||||
}
|
||||
@ -0,0 +1,16 @@
|
||||
import { Column, Entity, PrimaryColumn } from "../../../../../../src"
|
||||
|
||||
@Entity()
|
||||
export class BufferEmbedding {
|
||||
@PrimaryColumn()
|
||||
id: number
|
||||
|
||||
@Column("nclob")
|
||||
content: string
|
||||
|
||||
@Column("nclob")
|
||||
metadata: string
|
||||
|
||||
@Column("real_vector")
|
||||
realVector: Buffer
|
||||
}
|
||||
198
test/functional/database-schema/vectors/sap/sap-vector.ts
Normal file
198
test/functional/database-schema/vectors/sap/sap-vector.ts
Normal file
@ -0,0 +1,198 @@
|
||||
import { expect } from "chai"
|
||||
import { DataSource, DeepPartial } from "../../../../../src"
|
||||
import { DriverUtils } from "../../../../../src/driver/DriverUtils"
|
||||
import {
|
||||
closeTestingConnections,
|
||||
createTestingConnections,
|
||||
} from "../../../../utils/test-utils"
|
||||
import { ArrayEmbedding } from "./entity/ArrayEmbedding"
|
||||
import { BufferEmbedding } from "./entity/BufferEmbedding"
|
||||
|
||||
describe("database-schema > vectors > sap", () => {
|
||||
describe("with vector output type Array", () => {
|
||||
let dataSources: DataSource[]
|
||||
before(async () => {
|
||||
dataSources = await createTestingConnections({
|
||||
entities: [ArrayEmbedding],
|
||||
enabledDrivers: ["sap"],
|
||||
driverSpecific: {
|
||||
extra: {
|
||||
vectorOutputType: "Array",
|
||||
},
|
||||
synchronize: false,
|
||||
},
|
||||
})
|
||||
})
|
||||
after(() => closeTestingConnections(dataSources))
|
||||
|
||||
it("should work correctly - create, persist and hydrate", () =>
|
||||
Promise.all(
|
||||
dataSources.map(async (dataSource) => {
|
||||
if (
|
||||
!DriverUtils.isReleaseVersionOrGreater(
|
||||
dataSource.driver,
|
||||
"4.0",
|
||||
)
|
||||
) {
|
||||
return
|
||||
}
|
||||
|
||||
await dataSource.synchronize()
|
||||
|
||||
// Verify column metadata
|
||||
const queryRunner = await dataSource.createQueryRunner()
|
||||
const table = (await queryRunner.getTable(
|
||||
dataSource.getMetadata(ArrayEmbedding).tableName,
|
||||
))!
|
||||
await queryRunner.release()
|
||||
|
||||
expect(table.findColumnByName("smallVector")).to.contain({
|
||||
type: "real_vector",
|
||||
length: "16",
|
||||
})
|
||||
expect(table.findColumnByName("largeVector")).to.contain({
|
||||
type: "real_vector",
|
||||
length: "1536",
|
||||
isNullable: true,
|
||||
})
|
||||
expect(table.findColumnByName("variableVector")).to.contain(
|
||||
{
|
||||
type: "real_vector",
|
||||
length: "",
|
||||
},
|
||||
)
|
||||
|
||||
const smallVector = [
|
||||
0.004318627528846264, -0.008295782841742039,
|
||||
0.011462775990366936, -0.03171011060476303,
|
||||
-0.003404685528948903, 0.018827877938747406,
|
||||
0.010692788287997246, 0.014154385775327682,
|
||||
-0.026206370443105698, -0.03977154940366745,
|
||||
-0.008630559779703617, 0.040039367973804474,
|
||||
0.0019048830727115273, 0.01347813569009304,
|
||||
-0.02147931419312954, -0.004211498890072107,
|
||||
]
|
||||
const variableVector = [
|
||||
-0.0015692687593400478, -0.013364311307668686,
|
||||
0.013545091263949871, 0.034843627363443375,
|
||||
0.02682236023247242, -0.011710511520504951,
|
||||
0.0019400346791371703, -0.003324338933452964,
|
||||
0.004094745498150587, -0.01127530075609684,
|
||||
-0.020943669602274895, -0.018211888149380684,
|
||||
-0.00585190812125802, 0.01311657577753067,
|
||||
-0.011121302843093872, 0.003078277688473463,
|
||||
]
|
||||
|
||||
const plainEmbedding = {
|
||||
id: 1,
|
||||
content:
|
||||
"This is a sample text to be analyzed by SAP Joule AI",
|
||||
metadata: `{"client":"typeorm"}`,
|
||||
smallVector,
|
||||
largeVector: null,
|
||||
variableVector,
|
||||
} satisfies DeepPartial<ArrayEmbedding>
|
||||
|
||||
const embeddingRepository =
|
||||
dataSource.getRepository(ArrayEmbedding)
|
||||
const embedding = embeddingRepository.create(plainEmbedding)
|
||||
await embeddingRepository.save(embedding)
|
||||
|
||||
const loadedEmbedding = await embeddingRepository.findOneBy(
|
||||
{ id: 1 },
|
||||
)
|
||||
expect(loadedEmbedding).to.deep.equal(plainEmbedding)
|
||||
}),
|
||||
))
|
||||
})
|
||||
|
||||
describe("with vector output type Buffer", () => {
|
||||
let dataSources: DataSource[]
|
||||
before(async () => {
|
||||
dataSources = await createTestingConnections({
|
||||
entities: [BufferEmbedding],
|
||||
enabledDrivers: ["sap"],
|
||||
driverSpecific: {
|
||||
synchronize: false,
|
||||
},
|
||||
})
|
||||
})
|
||||
after(() => closeTestingConnections(dataSources))
|
||||
|
||||
function deserializeFvecs(buffer: Buffer) {
|
||||
const dataView = new DataView(
|
||||
buffer.buffer,
|
||||
buffer.byteOffset,
|
||||
buffer.byteLength,
|
||||
)
|
||||
const length = dataView.getUint32(0, true)
|
||||
const array = new Array<number>(length)
|
||||
for (let index = 0; index < length; index++) {
|
||||
array[index] = dataView.getFloat32(4 + index * 4, true)
|
||||
}
|
||||
|
||||
return array
|
||||
}
|
||||
|
||||
function serializeFvecs(array: number[]) {
|
||||
const length = array.length
|
||||
const arrayBuffer = new ArrayBuffer(4 + length * 4)
|
||||
const dataView = new DataView(arrayBuffer)
|
||||
|
||||
dataView.setUint32(0, length, true)
|
||||
for (let index = 0; index < length; index++) {
|
||||
dataView.setFloat32(4 + index * 4, array[index], true)
|
||||
}
|
||||
|
||||
return Buffer.from(arrayBuffer)
|
||||
}
|
||||
|
||||
it("should work correctly - persist and hydrate ", () =>
|
||||
Promise.all(
|
||||
dataSources.map(async (dataSource) => {
|
||||
if (
|
||||
!DriverUtils.isReleaseVersionOrGreater(
|
||||
dataSource.driver,
|
||||
"4.0",
|
||||
)
|
||||
) {
|
||||
return
|
||||
}
|
||||
|
||||
await dataSource.synchronize()
|
||||
|
||||
const plainVector = [
|
||||
-0.0015692687593400478, -0.013364311307668686,
|
||||
0.013545091263949871, 0.034843627363443375,
|
||||
0.02682236023247242, -0.011710511520504951,
|
||||
0.0019400346791371703, -0.003324338933452964,
|
||||
0.004094745498150587, -0.01127530075609684,
|
||||
-0.020943669602274895, -0.018211888149380684,
|
||||
-0.00585190812125802, 0.01311657577753067,
|
||||
-0.011121302843093872, 0.003078277688473463,
|
||||
]
|
||||
|
||||
const plainEmbedding = {
|
||||
id: 1,
|
||||
content:
|
||||
"This is a sample text to be analyzed by SAP Joule AI",
|
||||
metadata: `{"client":"typeorm"}`,
|
||||
realVector: serializeFvecs(plainVector),
|
||||
} satisfies DeepPartial<BufferEmbedding>
|
||||
|
||||
const embeddingRepository =
|
||||
dataSource.getRepository(BufferEmbedding)
|
||||
const embedding = embeddingRepository.create(plainEmbedding)
|
||||
await embeddingRepository.save(embedding)
|
||||
|
||||
const loadedEmbedding = await embeddingRepository.findOneBy(
|
||||
{ id: 1 },
|
||||
)
|
||||
const loadedVector = deserializeFvecs(
|
||||
loadedEmbedding!.realVector,
|
||||
)
|
||||
expect(loadedVector).to.deep.equal(plainVector)
|
||||
}),
|
||||
))
|
||||
})
|
||||
})
|
||||
Loading…
x
Reference in New Issue
Block a user