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This commit applies ormolu to the whole Haskell code base by running `make format`. For in-flight branches, simply merging changes from `main` will result in merge conflicts. To avoid this, update your branch using the following instructions. Replace `<format-commit>` by the hash of *this* commit. $ git checkout my-feature-branch $ git merge <format-commit>^ # and resolve conflicts normally $ make format $ git commit -a -m "reformat with ormolu" $ git merge -s ours post-ormolu https://github.com/hasura/graphql-engine-mono/pull/2404 GitOrigin-RevId: 75049f5c12f430c615eafb4c6b8e83e371e01c8e
540 lines
20 KiB
Haskell
540 lines
20 KiB
Haskell
-- | Multiplexed live query poller threads; see "Hasura.GraphQL.Execute.LiveQuery" for details.
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module Hasura.GraphQL.Execute.LiveQuery.Poll
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( -- * Pollers
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Poller (..),
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PollerId (..),
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PollerIOState (..),
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pollQuery,
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PollerKey (..),
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PollerMap,
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dumpPollerMap,
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PollDetails (..),
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BatchExecutionDetails (..),
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CohortExecutionDetails (..),
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LiveQueryPostPollHook,
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defaultLiveQueryPostPollHook,
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-- * Cohorts
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Cohort (..),
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CohortId,
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newCohortId,
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CohortVariables,
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CohortKey,
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CohortMap,
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-- * Subscribers
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Subscriber (..),
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SubscriberId,
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newSubscriberId,
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SubscriberMetadata,
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mkSubscriberMetadata,
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unSubscriberMetadata,
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SubscriberMap,
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OnChange,
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LGQResponse,
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LiveQueryResponse (..),
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LiveQueryMetadata (..),
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SubscriberExecutionDetails (..),
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-- * Batch
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BatchId (..),
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)
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where
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import Control.Concurrent.Async qualified as A
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import Control.Concurrent.STM qualified as STM
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import Control.Immortal qualified as Immortal
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import Control.Lens
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import Crypto.Hash qualified as CH
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import Data.Aeson.Extended qualified as J
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import Data.ByteString qualified as BS
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import Data.HashMap.Strict qualified as Map
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import Data.List.Split (chunksOf)
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import Data.Monoid (Sum (..))
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import Data.Text.Extended
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import Data.Time.Clock qualified as Clock
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import Data.UUID qualified as UUID
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import Data.UUID.V4 qualified as UUID
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import GHC.AssertNF.CPP
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import Hasura.Base.Error
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import Hasura.GraphQL.Execute.Backend
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import Hasura.GraphQL.Execute.LiveQuery.Options
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import Hasura.GraphQL.Execute.LiveQuery.Plan
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import Hasura.GraphQL.Execute.LiveQuery.TMap qualified as TMap
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import Hasura.GraphQL.ParameterizedQueryHash (ParameterizedQueryHash)
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import Hasura.GraphQL.Transport.Backend
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import Hasura.GraphQL.Transport.HTTP.Protocol
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import Hasura.GraphQL.Transport.WebSocket.Protocol (OperationId)
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import Hasura.GraphQL.Transport.WebSocket.Server qualified as WS
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import Hasura.Logging qualified as L
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import Hasura.Prelude
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import Hasura.RQL.Types.Backend
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import Hasura.RQL.Types.Common (SourceName, getNonNegativeInt)
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import Hasura.Server.Types (RequestId)
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import Hasura.Session
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import ListT qualified
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import StmContainers.Map qualified as STMMap
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-- ----------------------------------------------------------------------------------------------
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-- Subscribers
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newtype SubscriberId = SubscriberId {unSubscriberId :: UUID.UUID}
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deriving (Show, Eq, Generic, Hashable, J.ToJSON)
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newSubscriberId :: IO SubscriberId
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newSubscriberId =
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SubscriberId <$> UUID.nextRandom
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-- | Allows a user of the live query subsystem (currently websocket transport)
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-- to attach arbitrary metadata about a subscriber. This information is available
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-- as part of Subscriber in CohortExecutionDetails and can be logged by customizing
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-- in pollerlog
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newtype SubscriberMetadata = SubscriberMetadata {unSubscriberMetadata :: J.Value}
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deriving (Show, Eq, J.ToJSON)
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mkSubscriberMetadata :: WS.WSId -> OperationId -> Maybe OperationName -> RequestId -> SubscriberMetadata
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mkSubscriberMetadata websocketId operationId operationName reqId =
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SubscriberMetadata $
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J.object
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[ "websocket_id" J..= websocketId,
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"operation_id" J..= operationId,
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"operation_name" J..= operationName,
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"request_id" J..= reqId
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]
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data Subscriber = Subscriber
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{ _sId :: !SubscriberId,
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_sMetadata :: !SubscriberMetadata,
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_sRequestId :: !RequestId,
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_sOperationName :: !(Maybe OperationName),
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_sOnChangeCallback :: !OnChange
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}
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-- | live query onChange metadata, used for adding more extra analytics data
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data LiveQueryMetadata = LiveQueryMetadata
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{ _lqmExecutionTime :: !Clock.DiffTime
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}
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data LiveQueryResponse = LiveQueryResponse
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{ _lqrPayload :: !BS.ByteString,
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_lqrExecutionTime :: !Clock.DiffTime
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}
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type LGQResponse = GQResult LiveQueryResponse
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type OnChange = LGQResponse -> IO ()
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type SubscriberMap = TMap.TMap SubscriberId Subscriber
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-- -------------------------------------------------------------------------------------------------
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-- Cohorts
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-- | A batched group of 'Subscriber's who are not only listening to the same query but also have
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-- identical session and query variables. Each result pushed to a 'Cohort' is forwarded along to
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-- each of its 'Subscriber's.
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--
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-- In SQL, each 'Cohort' corresponds to a single row in the laterally-joined @_subs@ table (and
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-- therefore a single row in the query result).
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--
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-- See also 'CohortMap'.
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data Cohort = Cohort
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{ -- | a unique identifier used to identify the cohort in the generated query
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_cCohortId :: !CohortId,
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-- | a hash of the previous query result, if any, used to determine if we need to push an updated
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-- result to the subscribers or not
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_cPreviousResponse :: !(STM.TVar (Maybe ResponseHash)),
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-- | the subscribers we’ve already pushed a result to; we push new results to them iff the
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-- response changes
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_cExistingSubscribers :: !SubscriberMap,
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-- | subscribers we haven’t yet pushed any results to; we push results to them regardless if the
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-- result changed, then merge them in the map of existing subscribers
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_cNewSubscribers :: !SubscriberMap
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}
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-- | The @BatchId@ is a number based ID to uniquely identify a batch in a single poll and
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-- it's used to identify the batch to which a cohort belongs to.
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newtype BatchId = BatchId {_unBatchId :: Int}
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deriving (Show, Eq, J.ToJSON)
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{- Note [Blake2b faster than SHA-256]
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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At the time of writing, from https://blake2.net, it is stated,
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"BLAKE2 is a cryptographic hash function faster than MD5, SHA-1, SHA-2, and SHA-3,
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yet is at least as secure as the latest standard SHA-3".
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-}
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-- | A hash used to determine if the result changed without having to keep the entire result in
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-- memory. Using a cryptographic hash ensures that a hash collision is almost impossible: with 256
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-- bits, even if a subscription changes once per second for an entire year, the probability of a
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-- hash collision is ~4.294417×10-63. See Note [Blake2b faster than SHA-256].
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newtype ResponseHash = ResponseHash {unResponseHash :: CH.Digest CH.Blake2b_256}
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deriving (Show, Eq)
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instance J.ToJSON ResponseHash where
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toJSON = J.toJSON . show . unResponseHash
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mkRespHash :: BS.ByteString -> ResponseHash
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mkRespHash = ResponseHash . CH.hash
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-- | A key we use to determine if two 'Subscriber's belong in the same 'Cohort'
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-- (assuming they already meet the criteria to be in the same 'Poller'). Note
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-- the distinction between this and 'CohortId'; the latter is a completely
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-- synthetic key used only to identify the cohort in the generated SQL query.
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type CohortKey = CohortVariables
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-- | This has the invariant, maintained in 'removeLiveQuery', that it contains
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-- no 'Cohort' with zero total (existing + new) subscribers.
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type CohortMap = TMap.TMap CohortKey Cohort
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dumpCohortMap :: CohortMap -> IO J.Value
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dumpCohortMap cohortMap = do
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cohorts <- STM.atomically $ TMap.toList cohortMap
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fmap J.toJSON . forM cohorts $ \(variableValues, cohort) -> do
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cohortJ <- dumpCohort cohort
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return $
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J.object
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[ "variables" J..= variableValues,
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"cohort" J..= cohortJ
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]
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where
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dumpCohort (Cohort respId respTV curOps newOps) =
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STM.atomically $ do
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prevResHash <- STM.readTVar respTV
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curOpIds <- TMap.toList curOps
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newOpIds <- TMap.toList newOps
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return $
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J.object
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[ "resp_id" J..= respId,
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"current_ops" J..= map fst curOpIds,
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"new_ops" J..= map fst newOpIds,
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"previous_result_hash" J..= prevResHash
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]
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data CohortSnapshot = CohortSnapshot
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{ _csVariables :: !CohortVariables,
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_csPreviousResponse :: !(STM.TVar (Maybe ResponseHash)),
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_csExistingSubscribers :: ![Subscriber],
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_csNewSubscribers :: ![Subscriber]
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}
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pushResultToCohort ::
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GQResult BS.ByteString ->
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Maybe ResponseHash ->
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LiveQueryMetadata ->
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CohortSnapshot ->
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-- | subscribers to which data has been pushed, subscribers which already
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-- have this data (this information is exposed by metrics reporting)
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IO ([SubscriberExecutionDetails], [SubscriberExecutionDetails])
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pushResultToCohort result !respHashM (LiveQueryMetadata dTime) cohortSnapshot = do
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prevRespHashM <- STM.readTVarIO respRef
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-- write to the current websockets if needed
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(subscribersToPush, subscribersToIgnore) <-
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if isExecError result || respHashM /= prevRespHashM
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then do
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$assertNFHere respHashM -- so we don't write thunks to mutable vars
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STM.atomically $ STM.writeTVar respRef respHashM
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return (newSinks <> curSinks, mempty)
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else return (newSinks, curSinks)
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pushResultToSubscribers subscribersToPush
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pure $
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over
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(each . each)
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( \Subscriber {..} ->
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SubscriberExecutionDetails _sId _sMetadata
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)
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(subscribersToPush, subscribersToIgnore)
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where
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CohortSnapshot _ respRef curSinks newSinks = cohortSnapshot
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response = result <&> \payload -> LiveQueryResponse payload dTime
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pushResultToSubscribers =
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A.mapConcurrently_ $ \Subscriber {..} -> _sOnChangeCallback response
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-- -----------------------------------------------------------------------------
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-- Pollers
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-- | A unique, multiplexed query. Each 'Poller' has its own polling thread that
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-- periodically polls Postgres and pushes results to each of its listening
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-- 'Cohort's.
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--
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-- In SQL, an 'Poller' corresponds to a single, multiplexed query, though in
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-- practice, 'Poller's with large numbers of 'Cohort's are batched into
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-- multiple concurrent queries for performance reasons.
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data Poller = Poller
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{ _pCohorts :: !CohortMap,
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-- | This is in a separate 'STM.TMVar' because it’s important that we are
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-- able to construct 'Poller' values in 'STM.STM' --- we need the insertion
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-- into the 'PollerMap' to be atomic to ensure that we don’t accidentally
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-- create two for the same query due to a race. However, we can’t spawn the
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-- worker thread or create the metrics store in 'STM.STM', so we insert it
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-- into the 'Poller' only after we’re certain we won’t create any duplicates.
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--
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-- This var is "write once", moving monotonically from empty to full.
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-- TODO this could probably be tightened up to something like
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-- 'STM PollerIOState'
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_pIOState :: !(STM.TMVar PollerIOState)
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}
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data PollerIOState = PollerIOState
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{ -- | a handle on the poller’s worker thread that can be used to
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-- 'Immortal.stop' it if all its cohorts stop listening
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_pThread :: !Immortal.Thread,
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_pId :: !PollerId
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}
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data PollerKey =
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-- we don't need operation name here as a subscription will only have a
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-- single top level field
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PollerKey
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{ _lgSource :: !SourceName,
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_lgRole :: !RoleName,
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_lgQuery :: !Text
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}
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deriving (Show, Eq, Generic)
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instance Hashable PollerKey
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instance J.ToJSON PollerKey where
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toJSON (PollerKey source role query) =
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J.object
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[ "source" J..= source,
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"role" J..= role,
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"query" J..= query
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]
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type PollerMap = STMMap.Map PollerKey Poller
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dumpPollerMap :: Bool -> PollerMap -> IO J.Value
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dumpPollerMap extended lqMap =
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fmap J.toJSON $ do
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entries <- STM.atomically $ ListT.toList $ STMMap.listT lqMap
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forM entries $ \(PollerKey source role query, Poller cohortsMap ioState) -> do
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PollerIOState threadId pollerId <- STM.atomically $ STM.readTMVar ioState
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cohortsJ <-
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if extended
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then Just <$> dumpCohortMap cohortsMap
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else return Nothing
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return $
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J.object
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[ "source" J..= source,
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"role" J..= role,
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"thread_id" J..= show (Immortal.threadId threadId),
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"poller_id" J..= pollerId,
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"multiplexed_query" J..= query,
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"cohorts" J..= cohortsJ
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]
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-- | An ID to track unique 'Poller's, so that we can gather metrics about each
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-- poller
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newtype PollerId = PollerId {unPollerId :: UUID.UUID}
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deriving (Show, Eq, Generic, J.ToJSON)
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data SubscriberExecutionDetails = SubscriberExecutionDetails
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{ _sedSubscriberId :: !SubscriberId,
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_sedSubscriberMetadata :: !SubscriberMetadata
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}
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deriving (Show, Eq)
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-- | Execution information related to a cohort on a poll cycle
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data CohortExecutionDetails = CohortExecutionDetails
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{ _cedCohortId :: !CohortId,
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_cedVariables :: !CohortVariables,
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-- | Nothing in case of an error
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_cedResponseSize :: !(Maybe Int),
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-- | The response on this cycle has been pushed to these above subscribers
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-- New subscribers (those which haven't been around during the previous poll
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-- cycle) will always be part of this
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_cedPushedTo :: ![SubscriberExecutionDetails],
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-- | The response on this cycle has *not* been pushed to these above
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-- subscribers. This would when the response hasn't changed from the previous
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-- polled cycle
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_cedIgnored :: ![SubscriberExecutionDetails],
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_cedBatchId :: !BatchId
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}
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deriving (Show, Eq)
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-- | Execution information related to a single batched execution
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data BatchExecutionDetails = BatchExecutionDetails
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{ -- | postgres execution time of each batch
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_bedPgExecutionTime :: !Clock.DiffTime,
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-- | time to taken to push to all cohorts belonging to this batch
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_bedPushTime :: !Clock.DiffTime,
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-- | id of the batch
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_bedBatchId :: !BatchId,
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-- | execution details of the cohorts belonging to this batch
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_bedCohorts :: ![CohortExecutionDetails],
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_bedBatchResponseSizeBytes :: !(Maybe Int)
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}
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deriving (Show, Eq)
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-- | see Note [Minimal LiveQuery Poller Log]
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batchExecutionDetailMinimal :: BatchExecutionDetails -> J.Value
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batchExecutionDetailMinimal BatchExecutionDetails {..} =
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let batchRespSize =
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maybe
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mempty
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(\respSize -> ["batch_response_size_bytes" J..= respSize])
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_bedBatchResponseSizeBytes
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in J.object
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( [ "pg_execution_time" J..= _bedPgExecutionTime,
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"push_time" J..= _bedPushTime
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]
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-- log batch resp size only when there are no errors
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<> batchRespSize
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)
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data PollDetails = PollDetails
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{ -- | the unique ID (basically a thread that run as a 'Poller') for the
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-- 'Poller'
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_pdPollerId :: !PollerId,
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-- | the multiplexed SQL query to be run against the database with all the
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-- variables together
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_pdGeneratedSql :: !Text,
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-- | the time taken to get a snapshot of cohorts from our 'LiveQueriesState'
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-- data structure
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_pdSnapshotTime :: !Clock.DiffTime,
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-- | list of execution batches and their details
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_pdBatches :: ![BatchExecutionDetails],
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-- | total time spent on a poll cycle
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_pdTotalTime :: !Clock.DiffTime,
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_pdLiveQueryOptions :: !LiveQueriesOptions,
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_pdSource :: !SourceName,
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_pdRole :: !RoleName,
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_pdParameterizedQueryHash :: !ParameterizedQueryHash
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}
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deriving (Show, Eq)
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{- Note [Minimal LiveQuery Poller Log]
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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We only want to log the minimal information in the livequery-poller-log as it
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could be expensive to log the details of every subscriber (all poller related
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information can always be retrieved by dumping the current live queries state)
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We capture a lot more details in PollDetails and BatchExecutionDetails than
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that is logged currently as other implementations such as pro can use them if
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they need to.
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-}
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-- | see Note [Minimal LiveQuery Poller Log]
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pollDetailMinimal :: PollDetails -> J.Value
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pollDetailMinimal PollDetails {..} =
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J.object
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[ "poller_id" J..= _pdPollerId,
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"snapshot_time" J..= _pdSnapshotTime,
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"batches" J..= map batchExecutionDetailMinimal _pdBatches,
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"total_time" J..= _pdTotalTime,
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"source" J..= _pdSource,
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"role" J..= _pdRole
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]
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instance L.ToEngineLog PollDetails L.Hasura where
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toEngineLog pl = (L.LevelInfo, L.ELTLivequeryPollerLog, pollDetailMinimal pl)
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type LiveQueryPostPollHook = PollDetails -> IO ()
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-- the default LiveQueryPostPollHook
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defaultLiveQueryPostPollHook :: L.Logger L.Hasura -> LiveQueryPostPollHook
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defaultLiveQueryPostPollHook = L.unLogger
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-- | Where the magic happens: the top-level action run periodically by each
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-- active 'Poller'. This needs to be async exception safe.
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pollQuery ::
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forall b.
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BackendTransport b =>
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PollerId ->
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LiveQueriesOptions ->
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(SourceName, SourceConfig b) ->
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RoleName ->
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ParameterizedQueryHash ->
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MultiplexedQuery b ->
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CohortMap ->
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LiveQueryPostPollHook ->
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IO ()
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pollQuery pollerId lqOpts (sourceName, sourceConfig) roleName parameterizedQueryHash query cohortMap postPollHook = do
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(totalTime, (snapshotTime, batchesDetails)) <- withElapsedTime $ do
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-- snapshot the current cohorts and split them into batches
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(snapshotTime, cohortBatches) <- withElapsedTime $ do
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-- get a snapshot of all the cohorts
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-- this need not be done in a transaction
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cohorts <- STM.atomically $ TMap.toList cohortMap
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cohortSnapshots <- mapM (STM.atomically . getCohortSnapshot) cohorts
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-- cohorts are broken down into batches specified by the batch size
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let cohortBatches = chunksOf (getNonNegativeInt (unBatchSize batchSize)) cohortSnapshots
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-- associating every batch with their BatchId
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pure $ zip (BatchId <$> [1 ..]) cohortBatches
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-- concurrently process each batch
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batchesDetails <- A.forConcurrently cohortBatches $ \(batchId, cohorts) -> do
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(queryExecutionTime, mxRes) <- runDBSubscription @b sourceConfig query $ over (each . _2) _csVariables cohorts
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|
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let lqMeta = LiveQueryMetadata $ convertDuration queryExecutionTime
|
||
operations = getCohortOperations cohorts mxRes
|
||
-- batch response size is the sum of the response sizes of the cohorts
|
||
batchResponseSize =
|
||
case mxRes of
|
||
Left _ -> Nothing
|
||
Right resp -> Just $ getSum $ foldMap (Sum . BS.length . snd) resp
|
||
(pushTime, cohortsExecutionDetails) <- withElapsedTime $
|
||
A.forConcurrently operations $ \(res, cohortId, respData, snapshot) -> do
|
||
(pushedSubscribers, ignoredSubscribers) <-
|
||
pushResultToCohort res (fst <$> respData) lqMeta snapshot
|
||
pure
|
||
CohortExecutionDetails
|
||
{ _cedCohortId = cohortId,
|
||
_cedVariables = _csVariables snapshot,
|
||
_cedPushedTo = pushedSubscribers,
|
||
_cedIgnored = ignoredSubscribers,
|
||
_cedResponseSize = snd <$> respData,
|
||
_cedBatchId = batchId
|
||
}
|
||
pure $
|
||
BatchExecutionDetails
|
||
queryExecutionTime
|
||
pushTime
|
||
batchId
|
||
cohortsExecutionDetails
|
||
batchResponseSize
|
||
|
||
pure (snapshotTime, batchesDetails)
|
||
|
||
let pollDetails =
|
||
PollDetails
|
||
{ _pdPollerId = pollerId,
|
||
_pdGeneratedSql = toTxt query,
|
||
_pdSnapshotTime = snapshotTime,
|
||
_pdBatches = batchesDetails,
|
||
_pdLiveQueryOptions = lqOpts,
|
||
_pdTotalTime = totalTime,
|
||
_pdSource = sourceName,
|
||
_pdRole = roleName,
|
||
_pdParameterizedQueryHash = parameterizedQueryHash
|
||
}
|
||
postPollHook pollDetails
|
||
where
|
||
LiveQueriesOptions batchSize _ = lqOpts
|
||
|
||
getCohortSnapshot (cohortVars, handlerC) = do
|
||
let Cohort resId respRef curOpsTV newOpsTV = handlerC
|
||
curOpsL <- TMap.toList curOpsTV
|
||
newOpsL <- TMap.toList newOpsTV
|
||
forM_ newOpsL $ \(k, action) -> TMap.insert action k curOpsTV
|
||
TMap.reset newOpsTV
|
||
let cohortSnapshot = CohortSnapshot cohortVars respRef (map snd curOpsL) (map snd newOpsL)
|
||
return (resId, cohortSnapshot)
|
||
|
||
getCohortOperations cohorts = \case
|
||
Left e ->
|
||
-- TODO: this is internal error
|
||
let resp = throwError $ GQExecError [encodeGQLErr False e]
|
||
in [(resp, cohortId, Nothing, snapshot) | (cohortId, snapshot) <- cohorts]
|
||
Right responses -> do
|
||
let cohortSnapshotMap = Map.fromList cohorts
|
||
flip mapMaybe responses $ \(cohortId, respBS) ->
|
||
let respHash = mkRespHash respBS
|
||
respSize = BS.length respBS
|
||
in -- TODO: currently we ignore the cases when the cohortId from
|
||
-- Postgres response is not present in the cohort map of this batch
|
||
-- (this shouldn't happen but if it happens it means a logic error and
|
||
-- we should log it)
|
||
(pure respBS,cohortId,Just (respHash, respSize),)
|
||
<$> Map.lookup cohortId cohortSnapshotMap
|