Package com.google.spanner.v1

Class SpannerGrpc.SpannerBlockingStub

java.lang.Object
io.grpc.stub.AbstractStub<S>
io.grpc.stub.AbstractBlockingStub<SpannerGrpc.SpannerBlockingStub>
com.google.spanner.v1.SpannerGrpc.SpannerBlockingStub
Enclosing class:
SpannerGrpc
public static final class SpannerGrpc.SpannerBlockingStub extends io.grpc.stub.AbstractBlockingStub<SpannerGrpc.SpannerBlockingStub>
A stub to allow clients to do synchronous rpc calls to service Spanner. 
 Cloud Spanner API
 The Cloud Spanner API can be used to manage sessions and execute
 transactions on data stored in Cloud Spanner databases.

  • Method Details

    • build

      protected SpannerGrpc.SpannerBlockingStub build(io.grpc.Channel channel, io.grpc.CallOptions callOptions)
      Specified by:
      build in class io.grpc.stub.AbstractStub<SpannerGrpc.SpannerBlockingStub>

    • createSession

      public Session createSession(CreateSessionRequest request)
       Creates a new session. A session can be used to perform
 transactions that read and/or modify data in a Cloud Spanner database.
 Sessions are meant to be reused for many consecutive
 transactions.
 Sessions can only execute one transaction at a time. To execute
 multiple concurrent read-write/write-only transactions, create
 multiple sessions. Note that standalone reads and queries use a
 transaction internally, and count toward the one transaction
 limit.
 Active sessions use additional server resources, so it is a good idea to
 delete idle and unneeded sessions.
 Aside from explicit deletes, Cloud Spanner may delete sessions for which no
 operations are sent for more than an hour. If a session is deleted,
 requests to it return `NOT_FOUND`.
 Idle sessions can be kept alive by sending a trivial SQL query
 periodically, e.g., `"SELECT 1"`.

    • batchCreateSessions

      public BatchCreateSessionsResponse batchCreateSessions(BatchCreateSessionsRequest request)
       Creates multiple new sessions.
 This API can be used to initialize a session cache on the clients.
 See https://goo.gl/TgSFN2 for best practices on session cache management.

    • getSession

      public Session getSession(GetSessionRequest request)
       Gets a session. Returns `NOT_FOUND` if the session does not exist.
 This is mainly useful for determining whether a session is still
 alive.

    • listSessions

      public ListSessionsResponse listSessions(ListSessionsRequest request)
       Lists all sessions in a given database.

    • deleteSession

      public com.google.protobuf.Empty deleteSession(DeleteSessionRequest request)
       Ends a session, releasing server resources associated with it. This will
 asynchronously trigger cancellation of any operations that are running with
 this session.

    • executeSql

      public ResultSet executeSql(ExecuteSqlRequest request)
       Executes an SQL statement, returning all results in a single reply. This
 method cannot be used to return a result set larger than 10 MiB;
 if the query yields more data than that, the query fails with
 a `FAILED_PRECONDITION` error.
 Operations inside read-write transactions might return `ABORTED`. If
 this occurs, the application should restart the transaction from
 the beginning. See [Transaction][google.spanner.v1.Transaction] for more
 details.
 Larger result sets can be fetched in streaming fashion by calling
 [ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql]
 instead.

    • executeStreamingSql

      public Iterator<PartialResultSet> executeStreamingSql(ExecuteSqlRequest request)
       Like [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql], except returns the
 result set as a stream. Unlike
 [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql], there is no limit on
 the size of the returned result set. However, no individual row in the
 result set can exceed 100 MiB, and no column value can exceed 10 MiB.

    • executeBatchDml

      public ExecuteBatchDmlResponse executeBatchDml(ExecuteBatchDmlRequest request)
       Executes a batch of SQL DML statements. This method allows many statements
 to be run with lower latency than submitting them sequentially with
 [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql].
 Statements are executed in sequential order. A request can succeed even if
 a statement fails. The
 [ExecuteBatchDmlResponse.status][google.spanner.v1.ExecuteBatchDmlResponse.status]
 field in the response provides information about the statement that failed.
 Clients must inspect this field to determine whether an error occurred.
 Execution stops after the first failed statement; the remaining statements
 are not executed.

    • read

      public ResultSet read(ReadRequest request)
       Reads rows from the database using key lookups and scans, as a
 simple key/value style alternative to
 [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql].  This method cannot be
 used to return a result set larger than 10 MiB; if the read matches more
 data than that, the read fails with a `FAILED_PRECONDITION`
 error.
 Reads inside read-write transactions might return `ABORTED`. If
 this occurs, the application should restart the transaction from
 the beginning. See [Transaction][google.spanner.v1.Transaction] for more
 details.
 Larger result sets can be yielded in streaming fashion by calling
 [StreamingRead][google.spanner.v1.Spanner.StreamingRead] instead.

    • streamingRead

      public Iterator<PartialResultSet> streamingRead(ReadRequest request)
       Like [Read][google.spanner.v1.Spanner.Read], except returns the result set
 as a stream. Unlike [Read][google.spanner.v1.Spanner.Read], there is no
 limit on the size of the returned result set. However, no individual row in
 the result set can exceed 100 MiB, and no column value can exceed
 10 MiB.

    • beginTransaction

      public Transaction beginTransaction(BeginTransactionRequest request)
       Begins a new transaction. This step can often be skipped:
 [Read][google.spanner.v1.Spanner.Read],
 [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] and
 [Commit][google.spanner.v1.Spanner.Commit] can begin a new transaction as a
 side-effect.

    • commit

      public CommitResponse commit(CommitRequest request)
       Commits a transaction. The request includes the mutations to be
 applied to rows in the database.
 `Commit` might return an `ABORTED` error. This can occur at any time;
 commonly, the cause is conflicts with concurrent
 transactions. However, it can also happen for a variety of other
 reasons. If `Commit` returns `ABORTED`, the caller should re-attempt
 the transaction from the beginning, re-using the same session.
 On very rare occasions, `Commit` might return `UNKNOWN`. This can happen,
 for example, if the client job experiences a 1+ hour networking failure.
 At that point, Cloud Spanner has lost track of the transaction outcome and
 we recommend that you perform another read from the database to see the
 state of things as they are now.

    • rollback

      public com.google.protobuf.Empty rollback(RollbackRequest request)
       Rolls back a transaction, releasing any locks it holds. It is a good
 idea to call this for any transaction that includes one or more
 [Read][google.spanner.v1.Spanner.Read] or
 [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] requests and ultimately
 decides not to commit.
 `Rollback` returns `OK` if it successfully aborts the transaction, the
 transaction was already aborted, or the transaction is not
 found. `Rollback` never returns `ABORTED`.

    • partitionQuery

      public PartitionResponse partitionQuery(PartitionQueryRequest request)
       Creates a set of partition tokens that can be used to execute a query
 operation in parallel.  Each of the returned partition tokens can be used
 by [ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql] to
 specify a subset of the query result to read.  The same session and
 read-only transaction must be used by the PartitionQueryRequest used to
 create the partition tokens and the ExecuteSqlRequests that use the
 partition tokens.
 Partition tokens become invalid when the session used to create them
 is deleted, is idle for too long, begins a new transaction, or becomes too
 old.  When any of these happen, it is not possible to resume the query, and
 the whole operation must be restarted from the beginning.

    • partitionRead

      public PartitionResponse partitionRead(PartitionReadRequest request)
       Creates a set of partition tokens that can be used to execute a read
 operation in parallel.  Each of the returned partition tokens can be used
 by [StreamingRead][google.spanner.v1.Spanner.StreamingRead] to specify a
 subset of the read result to read.  The same session and read-only
 transaction must be used by the PartitionReadRequest used to create the
 partition tokens and the ReadRequests that use the partition tokens.  There
 are no ordering guarantees on rows returned among the returned partition
 tokens, or even within each individual StreamingRead call issued with a
 partition_token.
 Partition tokens become invalid when the session used to create them
 is deleted, is idle for too long, begins a new transaction, or becomes too
 old.  When any of these happen, it is not possible to resume the read, and
 the whole operation must be restarted from the beginning.

    • batchWrite

      public Iterator<BatchWriteResponse> batchWrite(BatchWriteRequest request)
       Batches the supplied mutation groups in a collection of efficient
 transactions. All mutations in a group are committed atomically. However,
 mutations across groups can be committed non-atomically in an unspecified
 order and thus, they must be independent of each other. Partial failure is
 possible, i.e., some groups may have been committed successfully, while
 some may have failed. The results of individual batches are streamed into
 the response as the batches are applied.
 BatchWrite requests are not replay protected, meaning that each mutation
 group may be applied more than once. Replays of non-idempotent mutations
 may have undesirable effects. For example, replays of an insert mutation
 may produce an already exists error or if you use generated or commit
 timestamp-based keys, it may result in additional rows being added to the
 mutation's table. We recommend structuring your mutation groups to be
 idempotent to avoid this issue.