graphql-engine/server/src-lib/Hasura/Backends/Postgres/DDL/Table.hs

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-- | Postgres DDL Table
--
-- Used to fill up the enum values field of 'Hasura.RQL.Types.Table.TableCoreInfoG'.
--
-- See 'Hasura.Eventing.Backend'.
module Hasura.Backends.Postgres.DDL.Table
( fetchAndValidateEnumValues,
)
where
import Control.Monad.Trans.Control (MonadBaseControl)
import Control.Monad.Validate
import Data.HashMap.Strict qualified as HashMap
import Data.List (delete)
import Data.List.NonEmpty qualified as NE
import Data.Sequence qualified as Seq
import Data.Sequence.NonEmpty qualified as NESeq
import Data.Text.Extended
import Database.PG.Query qualified as PG
import Hasura.Backends.Postgres.Connection
import Hasura.Backends.Postgres.SQL.DML
import Hasura.Backends.Postgres.SQL.Types
import Hasura.Base.Error
import Hasura.Prelude
import Hasura.RQL.Types.Backend
import Hasura.RQL.Types.BackendType
import Hasura.RQL.Types.Column
import Hasura.SQL.Types
import Hasura.Server.Utils
import Hasura.Table.Cache
import Language.GraphQL.Draft.Syntax qualified as G
data EnumTableIntegrityError (b :: BackendType)
= EnumTablePostgresError Text
| EnumTableMissingPrimaryKey
| EnumTableMultiColumnPrimaryKey [PGCol]
| EnumTableNonTextualPrimaryKey (RawColumnInfo b)
| EnumTableNoEnumValues
| EnumTableInvalidEnumValueNames (NE.NonEmpty Text)
| EnumTableNonTextualCommentColumn (RawColumnInfo b)
| EnumTableTooManyColumns [PGCol]
fetchAndValidateEnumValues ::
forall pgKind m.
(Backend ('Postgres pgKind), MonadIO m, MonadBaseControl IO m) =>
PGSourceConfig ->
QualifiedTable ->
Maybe (PrimaryKey ('Postgres pgKind) (RawColumnInfo ('Postgres pgKind))) ->
[RawColumnInfo ('Postgres pgKind)] ->
m (Either QErr EnumValues)
fetchAndValidateEnumValues pgSourceConfig tableName maybePrimaryKey columnInfos =
runExceptT $
either (throw400 ConstraintViolation . showErrors) pure =<< runValidateT fetchAndValidate
where
fetchAndValidate ::
(MonadIO n, MonadBaseControl IO n, MonadValidate [EnumTableIntegrityError ('Postgres pgKind)] n) =>
n EnumValues
fetchAndValidate = do
maybePrimaryKeyColumn <- tolerate validatePrimaryKey
maybeCommentColumn <- validateColumns maybePrimaryKeyColumn
case maybePrimaryKeyColumn of
Nothing -> refute mempty
Just primaryKeyColumn -> do
result <-
runPgSourceReadTx pgSourceConfig $
runValidateT $
fetchEnumValuesFromDb tableName primaryKeyColumn maybeCommentColumn
case result of
Left e -> (refute . pure . EnumTablePostgresError . qeError) e
Right (Left vErrs) -> refute vErrs
Right (Right r) -> pure r
where
validatePrimaryKey = case maybePrimaryKey of
Nothing -> refute [EnumTableMissingPrimaryKey]
Just primaryKey -> case _pkColumns primaryKey of
column NESeq.:<|| Seq.Empty -> case rciType column of
Nested array support for Data Connectors Backend and MongoDB ## Description This change adds support for querying into nested arrays in Data Connector agents that support such a concept (currently MongoDB). ### DC API changes - New API type `ColumnType` which allows representing the type of a "column" as either a scalar type, an object reference or an array of `ColumnType`s. This recursive definition allows arbitrary nesting of arrays of types. - The `type` fields in the API types `ColumnInfo` and `ColumnInsertSchema` now take a `ColumnType` instead of a `ScalarType`. - To ensure backwards compatibility, a `ColumnType` representing a scalar serialises and deserialises to the same representation as `ScalarType`. - In queries, the `Field` type now has a new constructor `NestedArrayField`. This contains a nested `Field` along with optional `limit`, `offset`, `where` and `order_by` arguments. (These optional arguments are not yet used by either HGE or the MongoDB agent.) ### MongoDB Haskell agent changes - The `/schema` endpoint will now recognise arrays within the JSON validation schema and generate corresponding arrays in the DC schema. - The `/query` endpoint will now handle `NestedArrayField`s within queries (although it does not yet handle `limit`, `offset`, `where` and `order_by`). ### HGE server changes - The `Backend` type class adds a new type family `XNestedArrays b` to enable nested arrays on a per-backend basis (currently enabled only for the `DataConnector` backend. - Within `RawColumnInfo` the column type is now represented by a new type `RawColumnType b` which mirrors the shape of the DC API `ColumnType`, but uses `XNestedObjects b` and `XNestedArrays b` type families to allow turning nested object and array supports on or off for a particular backend. In the `DataConnector` backend `API.CustomType` is converted into `RawColumnInfo 'DataConnector` while building the schema. - In the next stage of schema building, the `RawColumnInfo` is converted into a `StructuredColumnInfo` which allows us to represent the three different types of columns: scalar, object and array. TODO: the `StructuredColumnInfo` looks very similar to the Logical Model types. The main difference is that it uses the `XNestedObjects` and `XNestedArrays` type families. We should be able to combine these two representations. - The `StructuredColumnInfo` is then placed into a `FIColumn` `FieldInfo`. This involved some refactoring of `FieldInfo` as I had previously split out `FINestedObject` into a separate constructor. However it works out better to represent all "column" fields (i.e. scalar, object and array) using `FIColumn` as this make it easier to implement permission checking correctly. This is the reason the `StructuredColumnInfo` was needed. - Next, the `FieldInfo` are used to generate `FieldParser`s. We add a new constructor to `AnnFieldG` for `AFNestedArray`. An `AFNestedArray` field parser can contain either a simple array selection or an array aggregate. Simple array `FieldParsers` are currently limited to subfield selection. We will add support for limit, offset, where and order_by in a future PR. We also don't yet generate array aggregate `FieldParsers. - The new `AFNestedArray` field is handled by the `QueryPlan` module in the `DataConnector` backend. There we generate an `API.NestedArrayField` from the AFNestedArray. We also handle nested arrays when reshaping the response from the DC agent. ## Limitations - Support for limit, offset, filter (where) and order_by is not yet fully implemented, although it should not be hard to add this - Support for aggregations on nested arrays is not yet fully implemented - Permissions involving nested arrays (and objects) not yet implemented - This should be integrated with Logical Model types, but that will happen in a separate PR PR-URL: https://github.com/hasura/graphql-engine-mono/pull/9149 GitOrigin-RevId: 0e7b71a994fc1d2ca1ef73bfe7b96e95b5328531
2023-05-24 11:00:59 +03:00
RawColumnTypeScalar PGText -> pure column
_ -> refute [EnumTableNonTextualPrimaryKey column]
columns -> refute [EnumTableMultiColumnPrimaryKey $ map rciName (toList columns)]
validateColumns primaryKeyColumn = do
let nonPrimaryKeyColumns = maybe columnInfos (`delete` columnInfos) primaryKeyColumn
case nonPrimaryKeyColumns of
[] -> pure Nothing
[column] -> case rciType column of
Nested array support for Data Connectors Backend and MongoDB ## Description This change adds support for querying into nested arrays in Data Connector agents that support such a concept (currently MongoDB). ### DC API changes - New API type `ColumnType` which allows representing the type of a "column" as either a scalar type, an object reference or an array of `ColumnType`s. This recursive definition allows arbitrary nesting of arrays of types. - The `type` fields in the API types `ColumnInfo` and `ColumnInsertSchema` now take a `ColumnType` instead of a `ScalarType`. - To ensure backwards compatibility, a `ColumnType` representing a scalar serialises and deserialises to the same representation as `ScalarType`. - In queries, the `Field` type now has a new constructor `NestedArrayField`. This contains a nested `Field` along with optional `limit`, `offset`, `where` and `order_by` arguments. (These optional arguments are not yet used by either HGE or the MongoDB agent.) ### MongoDB Haskell agent changes - The `/schema` endpoint will now recognise arrays within the JSON validation schema and generate corresponding arrays in the DC schema. - The `/query` endpoint will now handle `NestedArrayField`s within queries (although it does not yet handle `limit`, `offset`, `where` and `order_by`). ### HGE server changes - The `Backend` type class adds a new type family `XNestedArrays b` to enable nested arrays on a per-backend basis (currently enabled only for the `DataConnector` backend. - Within `RawColumnInfo` the column type is now represented by a new type `RawColumnType b` which mirrors the shape of the DC API `ColumnType`, but uses `XNestedObjects b` and `XNestedArrays b` type families to allow turning nested object and array supports on or off for a particular backend. In the `DataConnector` backend `API.CustomType` is converted into `RawColumnInfo 'DataConnector` while building the schema. - In the next stage of schema building, the `RawColumnInfo` is converted into a `StructuredColumnInfo` which allows us to represent the three different types of columns: scalar, object and array. TODO: the `StructuredColumnInfo` looks very similar to the Logical Model types. The main difference is that it uses the `XNestedObjects` and `XNestedArrays` type families. We should be able to combine these two representations. - The `StructuredColumnInfo` is then placed into a `FIColumn` `FieldInfo`. This involved some refactoring of `FieldInfo` as I had previously split out `FINestedObject` into a separate constructor. However it works out better to represent all "column" fields (i.e. scalar, object and array) using `FIColumn` as this make it easier to implement permission checking correctly. This is the reason the `StructuredColumnInfo` was needed. - Next, the `FieldInfo` are used to generate `FieldParser`s. We add a new constructor to `AnnFieldG` for `AFNestedArray`. An `AFNestedArray` field parser can contain either a simple array selection or an array aggregate. Simple array `FieldParsers` are currently limited to subfield selection. We will add support for limit, offset, where and order_by in a future PR. We also don't yet generate array aggregate `FieldParsers. - The new `AFNestedArray` field is handled by the `QueryPlan` module in the `DataConnector` backend. There we generate an `API.NestedArrayField` from the AFNestedArray. We also handle nested arrays when reshaping the response from the DC agent. ## Limitations - Support for limit, offset, filter (where) and order_by is not yet fully implemented, although it should not be hard to add this - Support for aggregations on nested arrays is not yet fully implemented - Permissions involving nested arrays (and objects) not yet implemented - This should be integrated with Logical Model types, but that will happen in a separate PR PR-URL: https://github.com/hasura/graphql-engine-mono/pull/9149 GitOrigin-RevId: 0e7b71a994fc1d2ca1ef73bfe7b96e95b5328531
2023-05-24 11:00:59 +03:00
RawColumnTypeScalar PGText -> pure $ Just column
_ -> dispute [EnumTableNonTextualCommentColumn column] $> Nothing
columns -> dispute [EnumTableTooManyColumns $ map rciName columns] $> Nothing
showErrors :: [EnumTableIntegrityError ('Postgres pgKind)] -> Text
showErrors allErrors =
"the table " <> tableName <<> " cannot be used as an enum " <> reasonsMessage
where
reasonsMessage = makeReasonMessage allErrors showOne
showOne :: EnumTableIntegrityError ('Postgres pgKind) -> Text
showOne = \case
EnumTablePostgresError err -> "postgres error: " <> err
EnumTableMissingPrimaryKey -> "the table must have a primary key"
EnumTableMultiColumnPrimaryKey cols ->
"the tables primary key must not span multiple columns ("
<> commaSeparated (sort cols)
<> ")"
EnumTableNonTextualPrimaryKey colInfo -> typeMismatch "primary key" colInfo PGText
EnumTableNoEnumValues -> "the table must have at least one row"
EnumTableInvalidEnumValueNames values ->
let pluralString = " are not valid GraphQL enum value names"
valuesString = case NE.reverse (NE.sort values) of
value NE.:| [] -> "value " <> value <<> " is not a valid GraphQL enum value name"
value2 NE.:| [value1] -> "values " <> value1 <<> " and " <> value2 <<> pluralString
lastValue NE.:| otherValues ->
"values "
<> commaSeparated (reverse otherValues)
<> ", and "
<> lastValue <<> pluralString
in "the " <> valuesString
EnumTableNonTextualCommentColumn colInfo -> typeMismatch "comment column" colInfo PGText
EnumTableTooManyColumns cols ->
"the table must have exactly one primary key and optionally one comment column, not "
<> tshow (length cols)
<> " columns ("
<> commaSeparated (sort cols)
<> ")"
where
typeMismatch description colInfo expected =
Nested array support for Data Connectors Backend and MongoDB ## Description This change adds support for querying into nested arrays in Data Connector agents that support such a concept (currently MongoDB). ### DC API changes - New API type `ColumnType` which allows representing the type of a "column" as either a scalar type, an object reference or an array of `ColumnType`s. This recursive definition allows arbitrary nesting of arrays of types. - The `type` fields in the API types `ColumnInfo` and `ColumnInsertSchema` now take a `ColumnType` instead of a `ScalarType`. - To ensure backwards compatibility, a `ColumnType` representing a scalar serialises and deserialises to the same representation as `ScalarType`. - In queries, the `Field` type now has a new constructor `NestedArrayField`. This contains a nested `Field` along with optional `limit`, `offset`, `where` and `order_by` arguments. (These optional arguments are not yet used by either HGE or the MongoDB agent.) ### MongoDB Haskell agent changes - The `/schema` endpoint will now recognise arrays within the JSON validation schema and generate corresponding arrays in the DC schema. - The `/query` endpoint will now handle `NestedArrayField`s within queries (although it does not yet handle `limit`, `offset`, `where` and `order_by`). ### HGE server changes - The `Backend` type class adds a new type family `XNestedArrays b` to enable nested arrays on a per-backend basis (currently enabled only for the `DataConnector` backend. - Within `RawColumnInfo` the column type is now represented by a new type `RawColumnType b` which mirrors the shape of the DC API `ColumnType`, but uses `XNestedObjects b` and `XNestedArrays b` type families to allow turning nested object and array supports on or off for a particular backend. In the `DataConnector` backend `API.CustomType` is converted into `RawColumnInfo 'DataConnector` while building the schema. - In the next stage of schema building, the `RawColumnInfo` is converted into a `StructuredColumnInfo` which allows us to represent the three different types of columns: scalar, object and array. TODO: the `StructuredColumnInfo` looks very similar to the Logical Model types. The main difference is that it uses the `XNestedObjects` and `XNestedArrays` type families. We should be able to combine these two representations. - The `StructuredColumnInfo` is then placed into a `FIColumn` `FieldInfo`. This involved some refactoring of `FieldInfo` as I had previously split out `FINestedObject` into a separate constructor. However it works out better to represent all "column" fields (i.e. scalar, object and array) using `FIColumn` as this make it easier to implement permission checking correctly. This is the reason the `StructuredColumnInfo` was needed. - Next, the `FieldInfo` are used to generate `FieldParser`s. We add a new constructor to `AnnFieldG` for `AFNestedArray`. An `AFNestedArray` field parser can contain either a simple array selection or an array aggregate. Simple array `FieldParsers` are currently limited to subfield selection. We will add support for limit, offset, where and order_by in a future PR. We also don't yet generate array aggregate `FieldParsers. - The new `AFNestedArray` field is handled by the `QueryPlan` module in the `DataConnector` backend. There we generate an `API.NestedArrayField` from the AFNestedArray. We also handle nested arrays when reshaping the response from the DC agent. ## Limitations - Support for limit, offset, filter (where) and order_by is not yet fully implemented, although it should not be hard to add this - Support for aggregations on nested arrays is not yet fully implemented - Permissions involving nested arrays (and objects) not yet implemented - This should be integrated with Logical Model types, but that will happen in a separate PR PR-URL: https://github.com/hasura/graphql-engine-mono/pull/9149 GitOrigin-RevId: 0e7b71a994fc1d2ca1ef73bfe7b96e95b5328531
2023-05-24 11:00:59 +03:00
let RawColumnTypeScalar scalarType = rciType @('Postgres pgKind) colInfo
in "the tables "
<> description
<> " ("
<> rciName colInfo <<> ") must have type "
<> expected <<> ", not type " <>> scalarType
fetchEnumValuesFromDb ::
forall pgKind m.
(MonadTx m, MonadValidate [EnumTableIntegrityError ('Postgres pgKind)] m) =>
QualifiedTable ->
RawColumnInfo ('Postgres pgKind) ->
Maybe (RawColumnInfo ('Postgres pgKind)) ->
m EnumValues
fetchEnumValuesFromDb tableName primaryKeyColumn maybeCommentColumn = do
let nullExtr = Extractor SENull Nothing
commentExtr = maybe nullExtr (mkExtr . rciName) maybeCommentColumn
query =
PG.fromBuilder $
toSQL
mkSelect
{ selFrom = Just $ mkSimpleFromExp tableName,
selExtr = [mkExtr (rciName primaryKeyColumn), commentExtr]
}
rawEnumValues <- liftTx $ PG.withQE defaultTxErrorHandler query () True
when (null rawEnumValues) $ dispute [EnumTableNoEnumValues]
let enumValues = flip map rawEnumValues $
\(enumValueText, comment) ->
case mkValidEnumValueName enumValueText of
Nothing -> Left enumValueText
Just enumValue -> Right (EnumValue enumValue, EnumValueInfo comment)
badNames = lefts enumValues
validEnums = rights enumValues
case NE.nonEmpty badNames of
Just someBadNames -> refute [EnumTableInvalidEnumValueNames someBadNames]
Nothing -> pure $ HashMap.fromList validEnums
where
-- https://graphql.github.io/graphql-spec/June2018/#EnumValue
mkValidEnumValueName name =
if name `elem` ["true", "false", "null"]
then Nothing
else G.mkName name