As of January 1, 2020 this library no longer supports Python 2 on the latest released version.
Library versions released prior to that date will continue to be available. For more information please
visit Python 2 support on Google Cloud.
Source code for google.cloud.spanner_v1.types.transaction
# -*- coding: utf-8 -*-
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import proto # type: ignore
from google.protobuf import duration_pb2 # type: ignore
from google.protobuf import timestamp_pb2 # type: ignore
__protobuf__ = proto.module(
package="google.spanner.v1",
manifest={"TransactionOptions", "Transaction", "TransactionSelector",},
)
[docs]class TransactionOptions(proto.Message):
r"""Transactions:
Each session can have at most one active transaction at a time (note
that standalone reads and queries use a transaction internally and
do count towards the one transaction limit). After the active
transaction is completed, the session can immediately be re-used for
the next transaction. It is not necessary to create a new session
for each transaction.
Transaction Modes: Cloud Spanner supports three transaction modes:
1. Locking read-write. This type of transaction is the only way to
write data into Cloud Spanner. These transactions rely on
pessimistic locking and, if necessary, two-phase commit. Locking
read-write transactions may abort, requiring the application to
retry.
2. Snapshot read-only. This transaction type provides guaranteed
consistency across several reads, but does not allow writes.
Snapshot read-only transactions can be configured to read at
timestamps in the past. Snapshot read-only transactions do not
need to be committed.
3. Partitioned DML. This type of transaction is used to execute a
single Partitioned DML statement. Partitioned DML partitions the
key space and runs the DML statement over each partition in
parallel using separate, internal transactions that commit
independently. Partitioned DML transactions do not need to be
committed.
For transactions that only read, snapshot read-only transactions
provide simpler semantics and are almost always faster. In
particular, read-only transactions do not take locks, so they do not
conflict with read-write transactions. As a consequence of not
taking locks, they also do not abort, so retry loops are not needed.
Transactions may only read/write data in a single database. They
may, however, read/write data in different tables within that
database.
Locking Read-Write Transactions: Locking transactions may be used to
atomically read-modify-write data anywhere in a database. This type
of transaction is externally consistent.
Clients should attempt to minimize the amount of time a transaction
is active. Faster transactions commit with higher probability and
cause less contention. Cloud Spanner attempts to keep read locks
active as long as the transaction continues to do reads, and the
transaction has not been terminated by
[Commit][google.spanner.v1.Spanner.Commit] or
[Rollback][google.spanner.v1.Spanner.Rollback]. Long periods of
inactivity at the client may cause Cloud Spanner to release a
transaction's locks and abort it.
Conceptually, a read-write transaction consists of zero or more
reads or SQL statements followed by
[Commit][google.spanner.v1.Spanner.Commit]. At any time before
[Commit][google.spanner.v1.Spanner.Commit], the client can send a
[Rollback][google.spanner.v1.Spanner.Rollback] request to abort the
transaction.
Semantics: Cloud Spanner can commit the transaction if all read
locks it acquired are still valid at commit time, and it is able to
acquire write locks for all writes. Cloud Spanner can abort the
transaction for any reason. If a commit attempt returns ``ABORTED``,
Cloud Spanner guarantees that the transaction has not modified any
user data in Cloud Spanner.
Unless the transaction commits, Cloud Spanner makes no guarantees
about how long the transaction's locks were held for. It is an error
to use Cloud Spanner locks for any sort of mutual exclusion other
than between Cloud Spanner transactions themselves.
Retrying Aborted Transactions: When a transaction aborts, the
application can choose to retry the whole transaction again. To
maximize the chances of successfully committing the retry, the
client should execute the retry in the same session as the original
attempt. The original session's lock priority increases with each
consecutive abort, meaning that each attempt has a slightly better
chance of success than the previous.
Under some circumstances (for example, many transactions attempting
to modify the same row(s)), a transaction can abort many times in a
short period before successfully committing. Thus, it is not a good
idea to cap the number of retries a transaction can attempt;
instead, it is better to limit the total amount of time spent
retrying.
Idle Transactions: A transaction is considered idle if it has no
outstanding reads or SQL queries and has not started a read or SQL
query within the last 10 seconds. Idle transactions can be aborted
by Cloud Spanner so that they don't hold on to locks indefinitely.
If an idle transaction is aborted, the commit will fail with error
``ABORTED``.
If this behavior is undesirable, periodically executing a simple SQL
query in the transaction (for example, ``SELECT 1``) prevents the
transaction from becoming idle.
Snapshot Read-Only Transactions: Snapshot read-only transactions
provides a simpler method than locking read-write transactions for
doing several consistent reads. However, this type of transaction
does not support writes.
Snapshot transactions do not take locks. Instead, they work by
choosing a Cloud Spanner timestamp, then executing all reads at that
timestamp. Since they do not acquire locks, they do not block
concurrent read-write transactions.
Unlike locking read-write transactions, snapshot read-only
transactions never abort. They can fail if the chosen read timestamp
is garbage collected; however, the default garbage collection policy
is generous enough that most applications do not need to worry about
this in practice.
Snapshot read-only transactions do not need to call
[Commit][google.spanner.v1.Spanner.Commit] or
[Rollback][google.spanner.v1.Spanner.Rollback] (and in fact are not
permitted to do so).
To execute a snapshot transaction, the client specifies a timestamp
bound, which tells Cloud Spanner how to choose a read timestamp.
The types of timestamp bound are:
- Strong (the default).
- Bounded staleness.
- Exact staleness.
If the Cloud Spanner database to be read is geographically
distributed, stale read-only transactions can execute more quickly
than strong or read-write transaction, because they are able to
execute far from the leader replica.
Each type of timestamp bound is discussed in detail below.
Strong: Strong reads are guaranteed to see the effects of all
transactions that have committed before the start of the read.
Furthermore, all rows yielded by a single read are consistent with
each other -- if any part of the read observes a transaction, all
parts of the read see the transaction.
Strong reads are not repeatable: two consecutive strong read-only
transactions might return inconsistent results if there are
concurrent writes. If consistency across reads is required, the
reads should be executed within a transaction or at an exact read
timestamp.
See
[TransactionOptions.ReadOnly.strong][google.spanner.v1.TransactionOptions.ReadOnly.strong].
Exact Staleness: These timestamp bounds execute reads at a
user-specified timestamp. Reads at a timestamp are guaranteed to see
a consistent prefix of the global transaction history: they observe
modifications done by all transactions with a commit timestamp less
than or equal to the read timestamp, and observe none of the
modifications done by transactions with a larger commit timestamp.
They will block until all conflicting transactions that may be
assigned commit timestamps <= the read timestamp have finished.
The timestamp can either be expressed as an absolute Cloud Spanner
commit timestamp or a staleness relative to the current time.
These modes do not require a "negotiation phase" to pick a
timestamp. As a result, they execute slightly faster than the
equivalent boundedly stale concurrency modes. On the other hand,
boundedly stale reads usually return fresher results.
See
[TransactionOptions.ReadOnly.read_timestamp][google.spanner.v1.TransactionOptions.ReadOnly.read_timestamp]
and
[TransactionOptions.ReadOnly.exact_staleness][google.spanner.v1.TransactionOptions.ReadOnly.exact_staleness].
Bounded Staleness: Bounded staleness modes allow Cloud Spanner to
pick the read timestamp, subject to a user-provided staleness bound.
Cloud Spanner chooses the newest timestamp within the staleness
bound that allows execution of the reads at the closest available
replica without blocking.
All rows yielded are consistent with each other -- if any part of
the read observes a transaction, all parts of the read see the
transaction. Boundedly stale reads are not repeatable: two stale
reads, even if they use the same staleness bound, can execute at
different timestamps and thus return inconsistent results.
Boundedly stale reads execute in two phases: the first phase
negotiates a timestamp among all replicas needed to serve the read.
In the second phase, reads are executed at the negotiated timestamp.
As a result of the two phase execution, bounded staleness reads are
usually a little slower than comparable exact staleness reads.
However, they are typically able to return fresher results, and are
more likely to execute at the closest replica.
Because the timestamp negotiation requires up-front knowledge of
which rows will be read, it can only be used with single-use
read-only transactions.
See
[TransactionOptions.ReadOnly.max_staleness][google.spanner.v1.TransactionOptions.ReadOnly.max_staleness]
and
[TransactionOptions.ReadOnly.min_read_timestamp][google.spanner.v1.TransactionOptions.ReadOnly.min_read_timestamp].
Old Read Timestamps and Garbage Collection: Cloud Spanner
continuously garbage collects deleted and overwritten data in the
background to reclaim storage space. This process is known as
"version GC". By default, version GC reclaims versions after they
are one hour old. Because of this, Cloud Spanner cannot perform
reads at read timestamps more than one hour in the past. This
restriction also applies to in-progress reads and/or SQL queries
whose timestamp become too old while executing. Reads and SQL
queries with too-old read timestamps fail with the error
``FAILED_PRECONDITION``.
Partitioned DML Transactions: Partitioned DML transactions are used
to execute DML statements with a different execution strategy that
provides different, and often better, scalability properties for
large, table-wide operations than DML in a ReadWrite transaction.
Smaller scoped statements, such as an OLTP workload, should prefer
using ReadWrite transactions.
Partitioned DML partitions the keyspace and runs the DML statement
on each partition in separate, internal transactions. These
transactions commit automatically when complete, and run
independently from one another.
To reduce lock contention, this execution strategy only acquires
read locks on rows that match the WHERE clause of the statement.
Additionally, the smaller per-partition transactions hold locks for
less time.
That said, Partitioned DML is not a drop-in replacement for standard
DML used in ReadWrite transactions.
- The DML statement must be fully-partitionable. Specifically, the
statement must be expressible as the union of many statements
which each access only a single row of the table.
- The statement is not applied atomically to all rows of the table.
Rather, the statement is applied atomically to partitions of the
table, in independent transactions. Secondary index rows are
updated atomically with the base table rows.
- Partitioned DML does not guarantee exactly-once execution
semantics against a partition. The statement will be applied at
least once to each partition. It is strongly recommended that the
DML statement should be idempotent to avoid unexpected results.
For instance, it is potentially dangerous to run a statement such
as ``UPDATE table SET column = column + 1`` as it could be run
multiple times against some rows.
- The partitions are committed automatically - there is no support
for Commit or Rollback. If the call returns an error, or if the
client issuing the ExecuteSql call dies, it is possible that some
rows had the statement executed on them successfully. It is also
possible that statement was never executed against other rows.
- Partitioned DML transactions may only contain the execution of a
single DML statement via ExecuteSql or ExecuteStreamingSql.
- If any error is encountered during the execution of the
partitioned DML operation (for instance, a UNIQUE INDEX
violation, division by zero, or a value that cannot be stored due
to schema constraints), then the operation is stopped at that
point and an error is returned. It is possible that at this
point, some partitions have been committed (or even committed
multiple times), and other partitions have not been run at all.
Given the above, Partitioned DML is good fit for large,
database-wide, operations that are idempotent, such as deleting old
rows from a very large table.
This message has `oneof`_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Attributes:
read_write (google.cloud.spanner_v1.types.TransactionOptions.ReadWrite):
Transaction may write.
Authorization to begin a read-write transaction requires
``spanner.databases.beginOrRollbackReadWriteTransaction``
permission on the ``session`` resource.
This field is a member of `oneof`_ ``mode``.
partitioned_dml (google.cloud.spanner_v1.types.TransactionOptions.PartitionedDml):
Partitioned DML transaction.
Authorization to begin a Partitioned DML transaction
requires
``spanner.databases.beginPartitionedDmlTransaction``
permission on the ``session`` resource.
This field is a member of `oneof`_ ``mode``.
read_only (google.cloud.spanner_v1.types.TransactionOptions.ReadOnly):
Transaction will not write.
Authorization to begin a read-only transaction requires
``spanner.databases.beginReadOnlyTransaction`` permission on
the ``session`` resource.
This field is a member of `oneof`_ ``mode``.
"""
[docs] class ReadWrite(proto.Message):
r"""Message type to initiate a read-write transaction. Currently
this transaction type has no options.
"""
[docs] class PartitionedDml(proto.Message):
r"""Message type to initiate a Partitioned DML transaction.
"""
[docs] class ReadOnly(proto.Message):
r"""Message type to initiate a read-only transaction.
This message has `oneof`_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Attributes:
strong (bool):
Read at a timestamp where all previously
committed transactions are visible.
This field is a member of `oneof`_ ``timestamp_bound``.
min_read_timestamp (google.protobuf.timestamp_pb2.Timestamp):
Executes all reads at a timestamp >= ``min_read_timestamp``.
This is useful for requesting fresher data than some
previous read, or data that is fresh enough to observe the
effects of some previously committed transaction whose
timestamp is known.
Note that this option can only be used in single-use
transactions.
A timestamp in RFC3339 UTC "Zulu" format, accurate to
nanoseconds. Example: ``"2014-10-02T15:01:23.045123456Z"``.
This field is a member of `oneof`_ ``timestamp_bound``.
max_staleness (google.protobuf.duration_pb2.Duration):
Read data at a timestamp >= ``NOW - max_staleness`` seconds.
Guarantees that all writes that have committed more than the
specified number of seconds ago are visible. Because Cloud
Spanner chooses the exact timestamp, this mode works even if
the client's local clock is substantially skewed from Cloud
Spanner commit timestamps.
Useful for reading the freshest data available at a nearby
replica, while bounding the possible staleness if the local
replica has fallen behind.
Note that this option can only be used in single-use
transactions.
This field is a member of `oneof`_ ``timestamp_bound``.
read_timestamp (google.protobuf.timestamp_pb2.Timestamp):
Executes all reads at the given timestamp. Unlike other
modes, reads at a specific timestamp are repeatable; the
same read at the same timestamp always returns the same
data. If the timestamp is in the future, the read will block
until the specified timestamp, modulo the read's deadline.
Useful for large scale consistent reads such as mapreduces,
or for coordinating many reads against a consistent snapshot
of the data.
A timestamp in RFC3339 UTC "Zulu" format, accurate to
nanoseconds. Example: ``"2014-10-02T15:01:23.045123456Z"``.
This field is a member of `oneof`_ ``timestamp_bound``.
exact_staleness (google.protobuf.duration_pb2.Duration):
Executes all reads at a timestamp that is
``exact_staleness`` old. The timestamp is chosen soon after
the read is started.
Guarantees that all writes that have committed more than the
specified number of seconds ago are visible. Because Cloud
Spanner chooses the exact timestamp, this mode works even if
the client's local clock is substantially skewed from Cloud
Spanner commit timestamps.
Useful for reading at nearby replicas without the
distributed timestamp negotiation overhead of
``max_staleness``.
This field is a member of `oneof`_ ``timestamp_bound``.
return_read_timestamp (bool):
If true, the Cloud Spanner-selected read timestamp is
included in the [Transaction][google.spanner.v1.Transaction]
message that describes the transaction.
"""
strong = proto.Field(proto.BOOL, number=1, oneof="timestamp_bound",)
min_read_timestamp = proto.Field(
proto.MESSAGE,
number=2,
oneof="timestamp_bound",
message=timestamp_pb2.Timestamp,
)
max_staleness = proto.Field(
proto.MESSAGE,
number=3,
oneof="timestamp_bound",
message=duration_pb2.Duration,
)
read_timestamp = proto.Field(
proto.MESSAGE,
number=4,
oneof="timestamp_bound",
message=timestamp_pb2.Timestamp,
)
exact_staleness = proto.Field(
proto.MESSAGE,
number=5,
oneof="timestamp_bound",
message=duration_pb2.Duration,
)
return_read_timestamp = proto.Field(proto.BOOL, number=6,)
read_write = proto.Field(proto.MESSAGE, number=1, oneof="mode", message=ReadWrite,)
partitioned_dml = proto.Field(
proto.MESSAGE, number=3, oneof="mode", message=PartitionedDml,
)
read_only = proto.Field(proto.MESSAGE, number=2, oneof="mode", message=ReadOnly,)
[docs]class Transaction(proto.Message):
r"""A transaction.
Attributes:
id (bytes):
``id`` may be used to identify the transaction in subsequent
[Read][google.spanner.v1.Spanner.Read],
[ExecuteSql][google.spanner.v1.Spanner.ExecuteSql],
[Commit][google.spanner.v1.Spanner.Commit], or
[Rollback][google.spanner.v1.Spanner.Rollback] calls.
Single-use read-only transactions do not have IDs, because
single-use transactions do not support multiple requests.
read_timestamp (google.protobuf.timestamp_pb2.Timestamp):
For snapshot read-only transactions, the read timestamp
chosen for the transaction. Not returned by default: see
[TransactionOptions.ReadOnly.return_read_timestamp][google.spanner.v1.TransactionOptions.ReadOnly.return_read_timestamp].
A timestamp in RFC3339 UTC "Zulu" format, accurate to
nanoseconds. Example: ``"2014-10-02T15:01:23.045123456Z"``.
"""
id = proto.Field(proto.BYTES, number=1,)
read_timestamp = proto.Field(
proto.MESSAGE, number=2, message=timestamp_pb2.Timestamp,
)
[docs]class TransactionSelector(proto.Message):
r"""This message is used to select the transaction in which a
[Read][google.spanner.v1.Spanner.Read] or
[ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] call runs.
See [TransactionOptions][google.spanner.v1.TransactionOptions] for
more information about transactions.
This message has `oneof`_ fields (mutually exclusive fields).
For each oneof, at most one member field can be set at the same time.
Setting any member of the oneof automatically clears all other
members.
.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields
Attributes:
single_use (google.cloud.spanner_v1.types.TransactionOptions):
Execute the read or SQL query in a temporary
transaction. This is the most efficient way to
execute a transaction that consists of a single
SQL query.
This field is a member of `oneof`_ ``selector``.
id (bytes):
Execute the read or SQL query in a
previously-started transaction.
This field is a member of `oneof`_ ``selector``.
begin (google.cloud.spanner_v1.types.TransactionOptions):
Begin a new transaction and execute this read or SQL query
in it. The transaction ID of the new transaction is returned
in
[ResultSetMetadata.transaction][google.spanner.v1.ResultSetMetadata.transaction],
which is a [Transaction][google.spanner.v1.Transaction].
This field is a member of `oneof`_ ``selector``.
"""
single_use = proto.Field(
proto.MESSAGE, number=1, oneof="selector", message="TransactionOptions",
)
id = proto.Field(proto.BYTES, number=2, oneof="selector",)
begin = proto.Field(
proto.MESSAGE, number=3, oneof="selector", message="TransactionOptions",
)
__all__ = tuple(sorted(__protobuf__.manifest))