Spanner Client Types#

class google.cloud.spanner_v1.types.BeginTransactionRequest#

The request for [BeginTransaction][google.spanner.v1.Spanner.BeginTransaction].

session#

Required. The session in which the transaction runs.

options#

Required. Options for the new transaction.

options

Field google.spanner.v1.BeginTransactionRequest.options

session

Field google.spanner.v1.BeginTransactionRequest.session

class google.cloud.spanner_v1.types.CommitRequest#

The request for [Commit][google.spanner.v1.Spanner.Commit].

session#

Required. The session in which the transaction to be committed is running.

transaction#

Required. The transaction in which to commit.

transaction_id#

Commit a previously-started transaction.

single_use_transaction#

Execute mutations in a temporary transaction. Note that unlike commit of a previously-started transaction, commit with a temporary transaction is non-idempotent. That is, if the CommitRequest is sent to Cloud Spanner more than once (for instance, due to retries in the application, or in the transport library), it is possible that the mutations are executed more than once. If this is undesirable, use [BeginTransaction][google.spanner.v1.Spanner.BeginTransaction] and [Commit][google.spanner.v1.Spanner.Commit] instead.

mutations#

The mutations to be executed when this transaction commits. All mutations are applied atomically, in the order they appear in this list.

mutations

Field google.spanner.v1.CommitRequest.mutations

session

Field google.spanner.v1.CommitRequest.session

single_use_transaction

Field google.spanner.v1.CommitRequest.single_use_transaction

transaction_id

Field google.spanner.v1.CommitRequest.transaction_id

class google.cloud.spanner_v1.types.CommitResponse#

The response for [Commit][google.spanner.v1.Spanner.Commit].

commit_timestamp#

The Cloud Spanner timestamp at which the transaction committed.

commit_timestamp

Field google.spanner.v1.CommitResponse.commit_timestamp

class google.cloud.spanner_v1.types.CreateSessionRequest#

The request for [CreateSession][google.spanner.v1.Spanner.CreateSession].

database#

Required. The database in which the new session is created.

session#

The session to create.

database

Field google.spanner.v1.CreateSessionRequest.database

session

Field google.spanner.v1.CreateSessionRequest.session

class google.cloud.spanner_v1.types.CustomHttpPattern#
kind#

Field google.api.CustomHttpPattern.kind

path#

Field google.api.CustomHttpPattern.path

class google.cloud.spanner_v1.types.DeleteSessionRequest#

The request for [DeleteSession][google.spanner.v1.Spanner.DeleteSession].

name#

Required. The name of the session to delete.

name

Field google.spanner.v1.DeleteSessionRequest.name

class google.cloud.spanner_v1.types.DescriptorProto#
class ExtensionRange#
end#

Field google.protobuf.DescriptorProto.ExtensionRange.end

options#

Field google.protobuf.DescriptorProto.ExtensionRange.options

start#

Field google.protobuf.DescriptorProto.ExtensionRange.start

class ReservedRange#
end#

Field google.protobuf.DescriptorProto.ReservedRange.end

start#

Field google.protobuf.DescriptorProto.ReservedRange.start

enum_type#

Field google.protobuf.DescriptorProto.enum_type

extension#

Field google.protobuf.DescriptorProto.extension

extension_range#

Field google.protobuf.DescriptorProto.extension_range

field#

Field google.protobuf.DescriptorProto.field

name#

Field google.protobuf.DescriptorProto.name

nested_type#

Field google.protobuf.DescriptorProto.nested_type

oneof_decl#

Field google.protobuf.DescriptorProto.oneof_decl

options#

Field google.protobuf.DescriptorProto.options

reserved_name#

Field google.protobuf.DescriptorProto.reserved_name

reserved_range#

Field google.protobuf.DescriptorProto.reserved_range

class google.cloud.spanner_v1.types.Duration#
nanos#

Field google.protobuf.Duration.nanos

seconds#

Field google.protobuf.Duration.seconds

class google.cloud.spanner_v1.types.Empty#
class google.cloud.spanner_v1.types.EnumDescriptorProto#
class EnumReservedRange#
end#

Field google.protobuf.EnumDescriptorProto.EnumReservedRange.end

start#

Field google.protobuf.EnumDescriptorProto.EnumReservedRange.start

name#

Field google.protobuf.EnumDescriptorProto.name

options#

Field google.protobuf.EnumDescriptorProto.options

reserved_name#

Field google.protobuf.EnumDescriptorProto.reserved_name

reserved_range#

Field google.protobuf.EnumDescriptorProto.reserved_range

value#

Field google.protobuf.EnumDescriptorProto.value

class google.cloud.spanner_v1.types.EnumOptions#
allow_alias#

Field google.protobuf.EnumOptions.allow_alias

deprecated#

Field google.protobuf.EnumOptions.deprecated

uninterpreted_option#

Field google.protobuf.EnumOptions.uninterpreted_option

class google.cloud.spanner_v1.types.EnumValueDescriptorProto#
name#

Field google.protobuf.EnumValueDescriptorProto.name

number#

Field google.protobuf.EnumValueDescriptorProto.number

options#

Field google.protobuf.EnumValueDescriptorProto.options

class google.cloud.spanner_v1.types.EnumValueOptions#
deprecated#

Field google.protobuf.EnumValueOptions.deprecated

uninterpreted_option#

Field google.protobuf.EnumValueOptions.uninterpreted_option

class google.cloud.spanner_v1.types.ExecuteBatchDmlRequest#

The request for [ExecuteBatchDml][google.spanner.v1.Spanner.ExecuteBatchDml]

session#

Required. The session in which the DML statements should be performed.

transaction#

The transaction to use. A ReadWrite transaction is required. Single-use transactions are not supported (to avoid replay). The caller must either supply an existing transaction ID or begin a new transaction.

statements#

The list of statements to execute in this batch. Statements are executed serially, such that the effects of statement i are visible to statement i+1. Each statement must be a DML statement. Execution will stop at the first failed statement; the remaining statements will not run. REQUIRES: statements_size() > 0.

seqno#

A per-transaction sequence number used to identify this request. This is used in the same space as the seqno in [ExecuteSqlRequest][Spanner.ExecuteSqlRequest]. See more details in [ExecuteSqlRequest][Spanner.ExecuteSqlRequest].

class Statement#

A single DML statement.

sql#

Required. The DML string.

params#

The DML string can contain parameter placeholders. A parameter placeholder consists of '@' followed by the parameter name. Parameter names consist of any combination of letters, numbers, and underscores. Parameters can appear anywhere that a literal value is expected. The same parameter name can be used more than once, for example: "WHERE id > @msg_id AND id < @msg_id + 100" It is an error to execute an SQL statement with unbound parameters. Parameter values are specified using params, which is a JSON object whose keys are parameter names, and whose values are the corresponding parameter values.

param_types#

It is not always possible for Cloud Spanner to infer the right SQL type from a JSON value. For example, values of type BYTES and values of type STRING both appear in [params ][google.spanner.v1.ExecuteBatchDmlRequest.Statement.params] as JSON strings. In these cases, param_types can be used to specify the exact SQL type for some or all of the SQL statement parameters. See the definition of [Type][google.spanner.v1.Type] for more information about SQL types.

class ParamTypesEntry#
key#

Field google.spanner.v1.ExecuteBatchDmlRequest.Statement.ParamTypesEntry.key

value#

Field google.spanner.v1.ExecuteBatchDmlRequest.Statement.ParamTypesEntry.value

param_types

Field google.spanner.v1.ExecuteBatchDmlRequest.Statement.param_types

params

Field google.spanner.v1.ExecuteBatchDmlRequest.Statement.params

sql

Field google.spanner.v1.ExecuteBatchDmlRequest.Statement.sql

seqno

Field google.spanner.v1.ExecuteBatchDmlRequest.seqno

session

Field google.spanner.v1.ExecuteBatchDmlRequest.session

statements

Field google.spanner.v1.ExecuteBatchDmlRequest.statements

transaction

Field google.spanner.v1.ExecuteBatchDmlRequest.transaction

class google.cloud.spanner_v1.types.ExecuteBatchDmlResponse#

The response for [ExecuteBatchDml][google.spanner.v1.Spanner.ExecuteBatchDml]. Contains a list of [ResultSet][google.spanner.v1.ResultSet], one for each DML statement that has successfully executed. If a statement fails, the error is returned as part of the response payload. Clients can determine whether all DML statements have run successfully, or if a statement failed, using one of the following approaches:

  1. Check if ‘status’ field is OkStatus.

  2. Check if result_sets_size() equals the number of statements in [ExecuteBatchDmlRequest][Spanner.ExecuteBatchDmlRequest].

Example 1: A request with 5 DML statements, all executed successfully. Result: A response with 5 ResultSets, one for each statement in the same order, and an OK status.

Example 2: A request with 5 DML statements. The 3rd statement has a syntax error. Result: A response with 2 ResultSets, for the first 2 statements that run successfully, and a syntax error (INVALID_ARGUMENT) status. From result_set_size() client can determine that the 3rd statement has failed.

result_sets#

ResultSets, one for each statement in the request that ran successfully, in the same order as the statements in the request. Each [ResultSet][google.spanner.v1.ResultSet] will not contain any rows. The [ResultSetStats][google.spanner.v1.ResultSetStats] in each [ResultSet][google.spanner.v1.ResultSet] will contain the number of rows modified by the statement. Only the first ResultSet in the response contains a valid [ResultSetMetadata][google.spanner.v1.ResultSetMetadata].

status#

If all DML statements are executed successfully, status will be OK. Otherwise, the error status of the first failed statement.

result_sets

Field google.spanner.v1.ExecuteBatchDmlResponse.result_sets

status

Field google.spanner.v1.ExecuteBatchDmlResponse.status

class google.cloud.spanner_v1.types.ExecuteSqlRequest#

The request for [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] and [ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql].

session#

Required. The session in which the SQL query should be performed.

transaction#

The transaction to use. If none is provided, the default is a temporary read-only transaction with strong concurrency. The transaction to use. For queries, if none is provided, the default is a temporary read-only transaction with strong concurrency. Standard DML statements require a ReadWrite transaction. Single-use transactions are not supported (to avoid replay). The caller must either supply an existing transaction ID or begin a new transaction. Partitioned DML requires an existing PartitionedDml transaction ID.

sql#

Required. The SQL string.

params#

The SQL string can contain parameter placeholders. A parameter placeholder consists of '@' followed by the parameter name. Parameter names consist of any combination of letters, numbers, and underscores. Parameters can appear anywhere that a literal value is expected. The same parameter name can be used more than once, for example: "WHERE id > @msg_id AND id < @msg_id + 100" It is an error to execute an SQL statement with unbound parameters. Parameter values are specified using params, which is a JSON object whose keys are parameter names, and whose values are the corresponding parameter values.

param_types#

It is not always possible for Cloud Spanner to infer the right SQL type from a JSON value. For example, values of type BYTES and values of type STRING both appear in [params][google.spanner.v1.ExecuteSqlRequest.params] as JSON strings. In these cases, param_types can be used to specify the exact SQL type for some or all of the SQL statement parameters. See the definition of [Type][google.spanner.v1.Type] for more information about SQL types.

resume_token#

If this request is resuming a previously interrupted SQL statement execution, resume_token should be copied from the last [PartialResultSet][google.spanner.v1.PartialResultSet] yielded before the interruption. Doing this enables the new SQL statement execution to resume where the last one left off. The rest of the request parameters must exactly match the request that yielded this token.

query_mode#

Used to control the amount of debugging information returned in [ResultSetStats][google.spanner.v1.ResultSetStats]. If [par tition_token][google.spanner.v1.ExecuteSqlRequest.partition_ token] is set, [query_mode][google.spanner.v1.ExecuteSqlRequest.query_mode] can only be set to [QueryMode.NORMAL][google.spanner.v1.Execut eSqlRequest.QueryMode.NORMAL].

partition_token#

If present, results will be restricted to the specified partition previously created using PartitionQuery(). There must be an exact match for the values of fields common to this message and the PartitionQueryRequest message used to create this partition_token.

seqno#

A per-transaction sequence number used to identify this request. This makes each request idempotent such that if the request is received multiple times, at most one will succeed. The sequence number must be monotonically increasing within the transaction. If a request arrives for the first time with an out-of-order sequence number, the transaction may be aborted. Replays of previously handled requests will yield the same response as the first execution. Required for DML statements. Ignored for queries.

class ParamTypesEntry#
key#

Field google.spanner.v1.ExecuteSqlRequest.ParamTypesEntry.key

value#

Field google.spanner.v1.ExecuteSqlRequest.ParamTypesEntry.value

param_types

Field google.spanner.v1.ExecuteSqlRequest.param_types

params

Field google.spanner.v1.ExecuteSqlRequest.params

partition_token

Field google.spanner.v1.ExecuteSqlRequest.partition_token

query_mode

Field google.spanner.v1.ExecuteSqlRequest.query_mode

resume_token

Field google.spanner.v1.ExecuteSqlRequest.resume_token

seqno

Field google.spanner.v1.ExecuteSqlRequest.seqno

session

Field google.spanner.v1.ExecuteSqlRequest.session

sql

Field google.spanner.v1.ExecuteSqlRequest.sql

transaction

Field google.spanner.v1.ExecuteSqlRequest.transaction

class google.cloud.spanner_v1.types.ExtensionRangeOptions#
uninterpreted_option#

Field google.protobuf.ExtensionRangeOptions.uninterpreted_option

class google.cloud.spanner_v1.types.FieldDescriptorProto#
default_value#

Field google.protobuf.FieldDescriptorProto.default_value

extendee#

Field google.protobuf.FieldDescriptorProto.extendee

json_name#

Field google.protobuf.FieldDescriptorProto.json_name

label#

Field google.protobuf.FieldDescriptorProto.label

name#

Field google.protobuf.FieldDescriptorProto.name

number#

Field google.protobuf.FieldDescriptorProto.number

oneof_index#

Field google.protobuf.FieldDescriptorProto.oneof_index

options#

Field google.protobuf.FieldDescriptorProto.options

type#

Field google.protobuf.FieldDescriptorProto.type

type_name#

Field google.protobuf.FieldDescriptorProto.type_name

class google.cloud.spanner_v1.types.FieldOptions#
ctype#

Field google.protobuf.FieldOptions.ctype

deprecated#

Field google.protobuf.FieldOptions.deprecated

jstype#

Field google.protobuf.FieldOptions.jstype

lazy#

Field google.protobuf.FieldOptions.lazy

packed#

Field google.protobuf.FieldOptions.packed

uninterpreted_option#

Field google.protobuf.FieldOptions.uninterpreted_option

weak#

Field google.protobuf.FieldOptions.weak

class google.cloud.spanner_v1.types.FileDescriptorProto#
dependency#

Field google.protobuf.FileDescriptorProto.dependency

enum_type#

Field google.protobuf.FileDescriptorProto.enum_type

extension#

Field google.protobuf.FileDescriptorProto.extension

message_type#

Field google.protobuf.FileDescriptorProto.message_type

name#

Field google.protobuf.FileDescriptorProto.name

options#

Field google.protobuf.FileDescriptorProto.options

package#

Field google.protobuf.FileDescriptorProto.package

public_dependency#

Field google.protobuf.FileDescriptorProto.public_dependency

service#

Field google.protobuf.FileDescriptorProto.service

source_code_info#

Field google.protobuf.FileDescriptorProto.source_code_info

syntax#

Field google.protobuf.FileDescriptorProto.syntax

weak_dependency#

Field google.protobuf.FileDescriptorProto.weak_dependency

class google.cloud.spanner_v1.types.FileDescriptorSet#
file#

Field google.protobuf.FileDescriptorSet.file

class google.cloud.spanner_v1.types.FileOptions#
cc_enable_arenas#

Field google.protobuf.FileOptions.cc_enable_arenas

cc_generic_services#

Field google.protobuf.FileOptions.cc_generic_services

csharp_namespace#

Field google.protobuf.FileOptions.csharp_namespace

deprecated#

Field google.protobuf.FileOptions.deprecated

go_package#

Field google.protobuf.FileOptions.go_package

java_generate_equals_and_hash#

Field google.protobuf.FileOptions.java_generate_equals_and_hash

java_generic_services#

Field google.protobuf.FileOptions.java_generic_services

java_multiple_files#

Field google.protobuf.FileOptions.java_multiple_files

java_outer_classname#

Field google.protobuf.FileOptions.java_outer_classname

java_package#

Field google.protobuf.FileOptions.java_package

java_string_check_utf8#

Field google.protobuf.FileOptions.java_string_check_utf8

objc_class_prefix#

Field google.protobuf.FileOptions.objc_class_prefix

optimize_for#

Field google.protobuf.FileOptions.optimize_for

php_class_prefix#

Field google.protobuf.FileOptions.php_class_prefix

php_generic_services#

Field google.protobuf.FileOptions.php_generic_services

php_metadata_namespace#

Field google.protobuf.FileOptions.php_metadata_namespace

php_namespace#

Field google.protobuf.FileOptions.php_namespace

py_generic_services#

Field google.protobuf.FileOptions.py_generic_services

ruby_package#

Field google.protobuf.FileOptions.ruby_package

swift_prefix#

Field google.protobuf.FileOptions.swift_prefix

uninterpreted_option#

Field google.protobuf.FileOptions.uninterpreted_option

class google.cloud.spanner_v1.types.GeneratedCodeInfo#
class Annotation#
begin#

Field google.protobuf.GeneratedCodeInfo.Annotation.begin

end#

Field google.protobuf.GeneratedCodeInfo.Annotation.end

path#

Field google.protobuf.GeneratedCodeInfo.Annotation.path

source_file#

Field google.protobuf.GeneratedCodeInfo.Annotation.source_file

annotation#

Field google.protobuf.GeneratedCodeInfo.annotation

class google.cloud.spanner_v1.types.GetSessionRequest#

The request for [GetSession][google.spanner.v1.Spanner.GetSession].

name#

Required. The name of the session to retrieve.

name

Field google.spanner.v1.GetSessionRequest.name

class google.cloud.spanner_v1.types.Http#
fully_decode_reserved_expansion#

Field google.api.Http.fully_decode_reserved_expansion

rules#

Field google.api.Http.rules

class google.cloud.spanner_v1.types.HttpRule#
additional_bindings#

Field google.api.HttpRule.additional_bindings

body#

Field google.api.HttpRule.body

custom#

Field google.api.HttpRule.custom

delete#

Field google.api.HttpRule.delete

get#

Field google.api.HttpRule.get

patch#

Field google.api.HttpRule.patch

post#

Field google.api.HttpRule.post

put#

Field google.api.HttpRule.put

response_body#

Field google.api.HttpRule.response_body

selector#

Field google.api.HttpRule.selector

class google.cloud.spanner_v1.types.KeyRange#

KeyRange represents a range of rows in a table or index.

A range has a start key and an end key. These keys can be open or closed, indicating if the range includes rows with that key.

Keys are represented by lists, where the ith value in the list corresponds to the ith component of the table or index primary key. Individual values are encoded as described [here][google.spanner.v1.TypeCode].

For example, consider the following table definition:

CREATE TABLE UserEvents (
  UserName STRING(MAX),
  EventDate STRING(10)
) PRIMARY KEY(UserName, EventDate);

The following keys name rows in this table:

["Bob", "2014-09-23"]
["Alfred", "2015-06-12"]

Since the UserEvents table’s PRIMARY KEY clause names two columns, each UserEvents key has two elements; the first is the UserName, and the second is the EventDate.

Key ranges with multiple components are interpreted lexicographically by component using the table or index key’s declared sort order. For example, the following range returns all events for user "Bob" that occurred in the year 2015:

"start_closed": ["Bob", "2015-01-01"]
"end_closed": ["Bob", "2015-12-31"]

Start and end keys can omit trailing key components. This affects the inclusion and exclusion of rows that exactly match the provided key components: if the key is closed, then rows that exactly match the provided components are included; if the key is open, then rows that exactly match are not included.

For example, the following range includes all events for "Bob" that occurred during and after the year 2000:

"start_closed": ["Bob", "2000-01-01"]
"end_closed": ["Bob"]

The next example retrieves all events for "Bob":

"start_closed": ["Bob"]
"end_closed": ["Bob"]

To retrieve events before the year 2000:

"start_closed": ["Bob"]
"end_open": ["Bob", "2000-01-01"]

The following range includes all rows in the table:

"start_closed": []
"end_closed": []

This range returns all users whose UserName begins with any character from A to C:

"start_closed": ["A"]
"end_open": ["D"]

This range returns all users whose UserName begins with B:

"start_closed": ["B"]
"end_open": ["C"]

Key ranges honor column sort order. For example, suppose a table is defined as follows:

CREATE TABLE DescendingSortedTable {
  Key INT64,
  ...
) PRIMARY KEY(Key DESC);

The following range retrieves all rows with key values between 1 and 100 inclusive:

"start_closed": ["100"]
"end_closed": ["1"]

Note that 100 is passed as the start, and 1 is passed as the end, because Key is a descending column in the schema.

start_key_type#

The start key must be provided. It can be either closed or open.

start_closed#

If the start is closed, then the range includes all rows whose first len(start_closed) key columns exactly match start_closed.

start_open#

If the start is open, then the range excludes rows whose first len(start_open) key columns exactly match start_open.

end_key_type#

The end key must be provided. It can be either closed or open.

end_closed#

If the end is closed, then the range includes all rows whose first len(end_closed) key columns exactly match end_closed.

end_open#

If the end is open, then the range excludes rows whose first len(end_open) key columns exactly match end_open.

end_closed

Field google.spanner.v1.KeyRange.end_closed

end_open

Field google.spanner.v1.KeyRange.end_open

start_closed

Field google.spanner.v1.KeyRange.start_closed

start_open

Field google.spanner.v1.KeyRange.start_open

class google.cloud.spanner_v1.types.KeySet#

KeySet defines a collection of Cloud Spanner keys and/or key ranges. All the keys are expected to be in the same table or index. The keys need not be sorted in any particular way.

If the same key is specified multiple times in the set (for example if two ranges, two keys, or a key and a range overlap), Cloud Spanner behaves as if the key were only specified once.

keys#

A list of specific keys. Entries in keys should have exactly as many elements as there are columns in the primary or index key with which this KeySet is used. Individual key values are encoded as described [here][google.spanner.v1.TypeCode].

ranges#

A list of key ranges. See [KeyRange][google.spanner.v1.KeyRange] for more information about key range specifications.

all#

For convenience all can be set to true to indicate that this KeySet matches all keys in the table or index. Note that any keys specified in keys or ranges are only yielded once.

all

Field google.spanner.v1.KeySet.all

keys

Field google.spanner.v1.KeySet.keys

ranges

Field google.spanner.v1.KeySet.ranges

class google.cloud.spanner_v1.types.ListSessionsRequest#

The request for [ListSessions][google.spanner.v1.Spanner.ListSessions].

database#

Required. The database in which to list sessions.

page_size#

Number of sessions to be returned in the response. If 0 or less, defaults to the server’s maximum allowed page size.

page_token#

If non-empty, page_token should contain a [next_page_tok en][google.spanner.v1.ListSessionsResponse.next_page_token] from a previous [ListSessionsResponse][google.spanner.v1.ListS essionsResponse].

filter#

An expression for filtering the results of the request. Filter rules are case insensitive. The fields eligible for filtering are: - labels.key where key is the name of a label Some examples of using filters are: - labels.env:* –> The session has the label “env”. - labels.env:dev –> The session has the label “env” and the value of the label contains the string “dev”.

database

Field google.spanner.v1.ListSessionsRequest.database

filter

Field google.spanner.v1.ListSessionsRequest.filter

page_size

Field google.spanner.v1.ListSessionsRequest.page_size

page_token

Field google.spanner.v1.ListSessionsRequest.page_token

class google.cloud.spanner_v1.types.ListSessionsResponse#

The response for [ListSessions][google.spanner.v1.Spanner.ListSessions].

sessions#

The list of requested sessions.

next_page_token#

next_page_token can be sent in a subsequent [ListSessions][google.spanner.v1.Spanner.ListSessions] call to fetch more of the matching sessions.

next_page_token

Field google.spanner.v1.ListSessionsResponse.next_page_token

sessions

Field google.spanner.v1.ListSessionsResponse.sessions

class google.cloud.spanner_v1.types.ListValue#
values#

Field google.protobuf.ListValue.values

class google.cloud.spanner_v1.types.MessageOptions#
deprecated#

Field google.protobuf.MessageOptions.deprecated

map_entry#

Field google.protobuf.MessageOptions.map_entry

message_set_wire_format#

Field google.protobuf.MessageOptions.message_set_wire_format

no_standard_descriptor_accessor#

Field google.protobuf.MessageOptions.no_standard_descriptor_accessor

uninterpreted_option#

Field google.protobuf.MessageOptions.uninterpreted_option

class google.cloud.spanner_v1.types.MethodDescriptorProto#
client_streaming#

Field google.protobuf.MethodDescriptorProto.client_streaming

input_type#

Field google.protobuf.MethodDescriptorProto.input_type

name#

Field google.protobuf.MethodDescriptorProto.name

options#

Field google.protobuf.MethodDescriptorProto.options

output_type#

Field google.protobuf.MethodDescriptorProto.output_type

server_streaming#

Field google.protobuf.MethodDescriptorProto.server_streaming

class google.cloud.spanner_v1.types.MethodOptions#
deprecated#

Field google.protobuf.MethodOptions.deprecated

idempotency_level#

Field google.protobuf.MethodOptions.idempotency_level

uninterpreted_option#

Field google.protobuf.MethodOptions.uninterpreted_option

class google.cloud.spanner_v1.types.Mutation#

A modification to one or more Cloud Spanner rows. Mutations can be applied to a Cloud Spanner database by sending them in a [Commit][google.spanner.v1.Spanner.Commit] call.

operation#

Required. The operation to perform.

insert#

Insert new rows in a table. If any of the rows already exist, the write or transaction fails with error ALREADY_EXISTS.

update#

Update existing rows in a table. If any of the rows does not already exist, the transaction fails with error NOT_FOUND.

insert_or_update#

Like [insert][google.spanner.v1.Mutation.insert], except that if the row already exists, then its column values are overwritten with the ones provided. Any column values not explicitly written are preserved.

replace#

Like [insert][google.spanner.v1.Mutation.insert], except that if the row already exists, it is deleted, and the column values provided are inserted instead. Unlike [insert_or_upda te][google.spanner.v1.Mutation.insert_or_update], this means any values not explicitly written become NULL.

delete#

Delete rows from a table. Succeeds whether or not the named rows were present.

class Delete#

Arguments to [delete][google.spanner.v1.Mutation.delete] operations.

table#

Required. The table whose rows will be deleted.

key_set#

Required. The primary keys of the rows within [table][google.spanner.v1.Mutation.Delete.table] to delete. Delete is idempotent. The transaction will succeed even if some or all rows do not exist.

key_set

Field google.spanner.v1.Mutation.Delete.key_set

table

Field google.spanner.v1.Mutation.Delete.table

class Write#

Arguments to [insert][google.spanner.v1.Mutation.insert], [update][google.spanner.v1.Mutation.update], [insert_or_update][google.spanner.v1.Mutation.insert_or_update], and [replace][google.spanner.v1.Mutation.replace] operations.

table#

Required. The table whose rows will be written.

columns#

The names of the columns in [table][google.spanner.v1.Mutation.Write.table] to be written. The list of columns must contain enough columns to allow Cloud Spanner to derive values for all primary key columns in the row(s) to be modified.

values#

The values to be written. values can contain more than one list of values. If it does, then multiple rows are written, one for each entry in values. Each list in values must have exactly as many entries as there are entries in [columns][google.spanner.v1.Mutation.Write.columns] above. Sending multiple lists is equivalent to sending multiple Mutations, each containing one values entry and repeating [table][google.spanner.v1.Mutation.Write.table] and [columns][google.spanner.v1.Mutation.Write.columns]. Individual values in each list are encoded as described [here][google.spanner.v1.TypeCode].

columns

Field google.spanner.v1.Mutation.Write.columns

table

Field google.spanner.v1.Mutation.Write.table

values

Field google.spanner.v1.Mutation.Write.values

delete

Field google.spanner.v1.Mutation.delete

insert

Field google.spanner.v1.Mutation.insert

insert_or_update

Field google.spanner.v1.Mutation.insert_or_update

replace

Field google.spanner.v1.Mutation.replace

update

Field google.spanner.v1.Mutation.update

class google.cloud.spanner_v1.types.OneofDescriptorProto#
name#

Field google.protobuf.OneofDescriptorProto.name

options#

Field google.protobuf.OneofDescriptorProto.options

class google.cloud.spanner_v1.types.OneofOptions#
uninterpreted_option#

Field google.protobuf.OneofOptions.uninterpreted_option

class google.cloud.spanner_v1.types.PartialResultSet#

Partial results from a streaming read or SQL query. Streaming reads and SQL queries better tolerate large result sets, large rows, and large values, but are a little trickier to consume.

metadata#

Metadata about the result set, such as row type information. Only present in the first response.

values#

A streamed result set consists of a stream of values, which might be split into many PartialResultSet messages to accommodate large rows and/or large values. Every N complete values defines a row, where N is equal to the number of entries in [metadata.row_type.fields][google.spanner.v1.Struc tType.fields]. Most values are encoded based on type as described [here][google.spanner.v1.TypeCode]. It is possible that the last value in values is “chunked”, meaning that the rest of the value is sent in subsequent PartialResultSet (s). This is denoted by the [chunked_value][google.spanner.v1 .PartialResultSet.chunked_value] field. Two or more chunked values can be merged to form a complete value as follows: - bool/number/null: cannot be chunked - string: concatenate the strings - list: concatenate the lists. If the last element in a list is a string, list, or object, merge it with the first element in the next list by applying these rules recursively. - object: concatenate the (field name, field value) pairs. If a field name is duplicated, then apply these rules recursively to merge the field values. Some examples of merging: :: # Strings are concatenated. “foo”, “bar” => “foobar” # Lists of non-strings are concatenated. [2, 3], [4] => [2, 3, 4] # Lists are concatenated, but the last and first elements are merged # because they are strings. [“a”, “b”], [“c”, “d”] => [“a”, “bc”, “d”] # Lists are concatenated, but the last and first elements are merged # because they are lists. Recursively, the last and first elements # of the inner lists are merged because they are strings. [“a”, [“b”, “c”]], [[“d”], “e”] => [“a”, [“b”, “cd”], “e”] # Non-overlapping object fields are combined. {“a”: “1”}, {“b”: “2”} => {“a”: “1”, “b”: 2”} # Overlapping object fields are merged. {“a”: “1”}, {“a”: “2”} => {“a”: “12”} # Examples of merging objects containing lists of strings. {“a”: [“1”]}, {“a”: [“2”]} => {“a”: [“12”]} For a more complete example, suppose a streaming SQL query is yielding a result set whose rows contain a single string field. The following PartialResultSets might be yielded: :: { “metadata”: { … } “values”: [“Hello”, “W”] “chunked_value”: true “resume_token”: “Af65…” } { “values”: [“orl”] “chunked_value”: true “resume_token”: “Bqp2…” } { “values”: [“d”] “resume_token”: “Zx1B…” } This sequence of PartialResultSets encodes two rows, one containing the field value "Hello", and a second containing the field value "World" = "W" + "orl" + "d".

chunked_value#

If true, then the final value in [values][google.spanner.v1.PartialResultSet.values] is chunked, and must be combined with more values from subsequent PartialResultSets to obtain a complete field value.

resume_token#

Streaming calls might be interrupted for a variety of reasons, such as TCP connection loss. If this occurs, the stream of results can be resumed by re-sending the original request and including resume_token. Note that executing any other transaction in the same session invalidates the token.

stats#

Query plan and execution statistics for the statement that produced this streaming result set. These can be requested by setting [ExecuteSqlRequest.query_mode][google.spanner.v1.Exec uteSqlRequest.query_mode] and are sent only once with the last response in the stream. This field will also be present in the last response for DML statements.

chunked_value

Field google.spanner.v1.PartialResultSet.chunked_value

metadata

Field google.spanner.v1.PartialResultSet.metadata

resume_token

Field google.spanner.v1.PartialResultSet.resume_token

stats

Field google.spanner.v1.PartialResultSet.stats

values

Field google.spanner.v1.PartialResultSet.values

class google.cloud.spanner_v1.types.Partition#

Information returned for each partition returned in a PartitionResponse.

partition_token#

This token can be passed to Read, StreamingRead, ExecuteSql, or ExecuteStreamingSql requests to restrict the results to those identified by this partition token.

partition_token

Field google.spanner.v1.Partition.partition_token

class google.cloud.spanner_v1.types.PartitionOptions#

Options for a PartitionQueryRequest and PartitionReadRequest.

partition_size_bytes#

Note: This hint is currently ignored by PartitionQuery and PartitionRead requests. The desired data size for each partition generated. The default for this option is currently 1 GiB. This is only a hint. The actual size of each partition may be smaller or larger than this size request.

max_partitions#

Note: This hint is currently ignored by PartitionQuery and PartitionRead requests. The desired maximum number of partitions to return. For example, this may be set to the number of workers available. The default for this option is currently 10,000. The maximum value is currently 200,000. This is only a hint. The actual number of partitions returned may be smaller or larger than this maximum count request.

max_partitions

Field google.spanner.v1.PartitionOptions.max_partitions

partition_size_bytes

Field google.spanner.v1.PartitionOptions.partition_size_bytes

class google.cloud.spanner_v1.types.PartitionQueryRequest#

The request for [PartitionQuery][google.spanner.v1.Spanner.PartitionQuery]

session#

Required. The session used to create the partitions.

transaction#

Read only snapshot transactions are supported, read/write and single use transactions are not.

sql#

The query request to generate partitions for. The request will fail if the query is not root partitionable. The query plan of a root partitionable query has a single distributed union operator. A distributed union operator conceptually divides one or more tables into multiple splits, remotely evaluates a subquery independently on each split, and then unions all results. This must not contain DML commands, such as INSERT, UPDATE, or DELETE. Use [ExecuteStreamingSql][google.spanner.v1 .Spanner.ExecuteStreamingSql] with a PartitionedDml transaction for large, partition-friendly DML operations.

params#

The SQL query string can contain parameter placeholders. A parameter placeholder consists of '@' followed by the parameter name. Parameter names consist of any combination of letters, numbers, and underscores. Parameters can appear anywhere that a literal value is expected. The same parameter name can be used more than once, for example: "WHERE id > @msg_id AND id < @msg_id + 100" It is an error to execute an SQL query with unbound parameters. Parameter values are specified using params, which is a JSON object whose keys are parameter names, and whose values are the corresponding parameter values.

param_types#

It is not always possible for Cloud Spanner to infer the right SQL type from a JSON value. For example, values of type BYTES and values of type STRING both appear in [params][google.spanner.v1.PartitionQueryRequest.params] as JSON strings. In these cases, param_types can be used to specify the exact SQL type for some or all of the SQL query parameters. See the definition of [Type][google.spanner.v1.Type] for more information about SQL types.

partition_options#

Additional options that affect how many partitions are created.

class ParamTypesEntry#
key#

Field google.spanner.v1.PartitionQueryRequest.ParamTypesEntry.key

value#

Field google.spanner.v1.PartitionQueryRequest.ParamTypesEntry.value

param_types

Field google.spanner.v1.PartitionQueryRequest.param_types

params

Field google.spanner.v1.PartitionQueryRequest.params

partition_options

Field google.spanner.v1.PartitionQueryRequest.partition_options

session

Field google.spanner.v1.PartitionQueryRequest.session

sql

Field google.spanner.v1.PartitionQueryRequest.sql

transaction

Field google.spanner.v1.PartitionQueryRequest.transaction

class google.cloud.spanner_v1.types.PartitionReadRequest#

The request for [PartitionRead][google.spanner.v1.Spanner.PartitionRead]

session#

Required. The session used to create the partitions.

transaction#

Read only snapshot transactions are supported, read/write and single use transactions are not.

table#

Required. The name of the table in the database to be read.

index#

If non-empty, the name of an index on [table][google.spanner.v1.PartitionReadRequest.table]. This index is used instead of the table primary key when interpreting [key_set][google.spanner.v1.PartitionReadRequest.key_set] and sorting result rows. See [key_set][google.spanner.v1.PartitionReadRequest.key_set] for further information.

columns#

The columns of [table][google.spanner.v1.PartitionReadRequest.table] to be returned for each row matching this request.

key_set#

Required. key_set identifies the rows to be yielded. key_set names the primary keys of the rows in [table][google.spanner.v1.PartitionReadRequest.table] to be yielded, unless [index][google.spanner.v1.PartitionReadRequest.index] is present. If [index][google.spanner.v1.PartitionReadRequest.index] is present, then [key_set][google.spanner.v1.PartitionReadRequest.key_set] instead names index keys in [index][google.spanner.v1.PartitionReadRequest.index]. It is not an error for the key_set to name rows that do not exist in the database. Read yields nothing for nonexistent rows.

partition_options#

Additional options that affect how many partitions are created.

columns

Field google.spanner.v1.PartitionReadRequest.columns

index

Field google.spanner.v1.PartitionReadRequest.index

key_set

Field google.spanner.v1.PartitionReadRequest.key_set

partition_options

Field google.spanner.v1.PartitionReadRequest.partition_options

session

Field google.spanner.v1.PartitionReadRequest.session

table

Field google.spanner.v1.PartitionReadRequest.table

transaction

Field google.spanner.v1.PartitionReadRequest.transaction

class google.cloud.spanner_v1.types.PartitionResponse#

The response for [PartitionQuery][google.spanner.v1.Spanner.PartitionQuery] or [PartitionRead][google.spanner.v1.Spanner.PartitionRead]

partitions#

Partitions created by this request.

transaction#

Transaction created by this request.

partitions

Field google.spanner.v1.PartitionResponse.partitions

transaction

Field google.spanner.v1.PartitionResponse.transaction

class google.cloud.spanner_v1.types.PlanNode#

Node information for nodes appearing in a [QueryPlan.plan_nodes][google.spanner.v1.QueryPlan.plan_nodes].

index#

The PlanNode’s index in [node list][google.spanner.v1.QueryPlan.plan_nodes].

kind#

Used to determine the type of node. May be needed for visualizing different kinds of nodes differently. For example, If the node is a [SCALAR][google.spanner.v1.PlanNode.Kind.SCALAR] node, it will have a condensed representation which can be used to directly embed a description of the node in its parent.

display_name#

The display name for the node.

List of child node indexes and their relationship to this parent.

short_representation#

Condensed representation for [SCALAR][google.spanner.v1.PlanNode.Kind.SCALAR] nodes.

metadata#

Attributes relevant to the node contained in a group of key- value pairs. For example, a Parameter Reference node could have the following information in its metadata: :: { “parameter_reference”: “param1”, “parameter_type”: “array” }

execution_stats#

The execution statistics associated with the node, contained in a group of key-value pairs. Only present if the plan was returned as a result of a profile query. For example, number of executions, number of rows/time per execution etc.

Metadata associated with a parent-child relationship appearing in a [PlanNode][google.spanner.v1.PlanNode].

child_index#

The node to which the link points.

type#

The type of the link. For example, in Hash Joins this could be used to distinguish between the build child and the probe child, or in the case of the child being an output variable, to represent the tag associated with the output variable.

variable#

Only present if the child node is [SCALAR][google.spanner.v1.PlanNode.Kind.SCALAR] and corresponds to an output variable of the parent node. The field carries the name of the output variable. For example, a TableScan operator that reads rows from a table will have child links to the SCALAR nodes representing the output variables created for each column that is read by the operator. The corresponding variable fields will be set to the variable names assigned to the columns.

child_index

Field google.spanner.v1.PlanNode.ChildLink.child_index

type

Field google.spanner.v1.PlanNode.ChildLink.type

variable

Field google.spanner.v1.PlanNode.ChildLink.variable

class ShortRepresentation#

Condensed representation of a node and its subtree. Only present for SCALAR [PlanNode(s)][google.spanner.v1.PlanNode].

description#

A string representation of the expression subtree rooted at this node.

subqueries#

A mapping of (subquery variable name) -> (subquery node id) for cases where the description string of this node references a SCALAR subquery contained in the expression subtree rooted at this node. The referenced SCALAR subquery may not necessarily be a direct child of this node.

class SubqueriesEntry#
key#

Field google.spanner.v1.PlanNode.ShortRepresentation.SubqueriesEntry.key

value#

Field google.spanner.v1.PlanNode.ShortRepresentation.SubqueriesEntry.value

description

Field google.spanner.v1.PlanNode.ShortRepresentation.description

subqueries

Field google.spanner.v1.PlanNode.ShortRepresentation.subqueries

child_links

Field google.spanner.v1.PlanNode.child_links

display_name

Field google.spanner.v1.PlanNode.display_name

execution_stats

Field google.spanner.v1.PlanNode.execution_stats

index

Field google.spanner.v1.PlanNode.index

kind

Field google.spanner.v1.PlanNode.kind

metadata

Field google.spanner.v1.PlanNode.metadata

short_representation

Field google.spanner.v1.PlanNode.short_representation

class google.cloud.spanner_v1.types.QueryPlan#

Contains an ordered list of nodes appearing in the query plan.

plan_nodes#

The nodes in the query plan. Plan nodes are returned in pre- order starting with the plan root. Each [PlanNode][google.spanner.v1.PlanNode]’s id corresponds to its index in plan_nodes.

plan_nodes

Field google.spanner.v1.QueryPlan.plan_nodes

class google.cloud.spanner_v1.types.ReadRequest#

The request for [Read][google.spanner.v1.Spanner.Read] and [StreamingRead][google.spanner.v1.Spanner.StreamingRead].

session#

Required. The session in which the read should be performed.

transaction#

The transaction to use. If none is provided, the default is a temporary read-only transaction with strong concurrency.

table#

Required. The name of the table in the database to be read.

index#

If non-empty, the name of an index on [table][google.spanner.v1.ReadRequest.table]. This index is used instead of the table primary key when interpreting [key_set][google.spanner.v1.ReadRequest.key_set] and sorting result rows. See [key_set][google.spanner.v1.ReadRequest.key_set] for further information.

columns#

The columns of [table][google.spanner.v1.ReadRequest.table] to be returned for each row matching this request.

key_set#

Required. key_set identifies the rows to be yielded. key_set names the primary keys of the rows in [table][google.spanner.v1.ReadRequest.table] to be yielded, unless [index][google.spanner.v1.ReadRequest.index] is present. If [index][google.spanner.v1.ReadRequest.index] is present, then [key_set][google.spanner.v1.ReadRequest.key_set] instead names index keys in [index][google.spanner.v1.ReadRequest.index]. If the [partiti on_token][google.spanner.v1.ReadRequest.partition_token] field is empty, rows are yielded in table primary key order (if [index][google.spanner.v1.ReadRequest.index] is empty) or index key order (if [index][google.spanner.v1.ReadRequest.index] is non-empty). If the [partition_token][google.spanner.v1.ReadRequest.partition _token] field is not empty, rows will be yielded in an unspecified order. It is not an error for the key_set to name rows that do not exist in the database. Read yields nothing for nonexistent rows.

limit#

If greater than zero, only the first limit rows are yielded. If limit is zero, the default is no limit. A limit cannot be specified if partition_token is set.

resume_token#

If this request is resuming a previously interrupted read, resume_token should be copied from the last [PartialResultSet][google.spanner.v1.PartialResultSet] yielded before the interruption. Doing this enables the new read to resume where the last read left off. The rest of the request parameters must exactly match the request that yielded this token.

partition_token#

If present, results will be restricted to the specified partition previously created using PartitionRead(). There must be an exact match for the values of fields common to this message and the PartitionReadRequest message used to create this partition_token.

columns

Field google.spanner.v1.ReadRequest.columns

index

Field google.spanner.v1.ReadRequest.index

key_set

Field google.spanner.v1.ReadRequest.key_set

limit

Field google.spanner.v1.ReadRequest.limit

partition_token

Field google.spanner.v1.ReadRequest.partition_token

resume_token

Field google.spanner.v1.ReadRequest.resume_token

session

Field google.spanner.v1.ReadRequest.session

table

Field google.spanner.v1.ReadRequest.table

transaction

Field google.spanner.v1.ReadRequest.transaction

class google.cloud.spanner_v1.types.ResultSet#

Results from [Read][google.spanner.v1.Spanner.Read] or [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql].

metadata#

Metadata about the result set, such as row type information.

rows#

Each element in rows is a row whose format is defined by [ metadata.row_type][google.spanner.v1.ResultSetMetadata.row_t ype]. The ith element in each row matches the ith field in [me tadata.row_type][google.spanner.v1.ResultSetMetadata.row_typ e]. Elements are encoded based on type as described [here][google.spanner.v1.TypeCode].

stats#

Query plan and execution statistics for the SQL statement that produced this result set. These can be requested by setting [E xecuteSqlRequest.query_mode][google.spanner.v1.ExecuteSqlRequ est.query_mode]. DML statements always produce stats containing the number of rows modified, unless executed using the [ExecuteSqlRequest.QueryMode.PLAN][google.spanner.v1.Execu teSqlRequest.QueryMode.PLAN] [ExecuteSqlRequest.query_mode][g oogle.spanner.v1.ExecuteSqlRequest.query_mode]. Other fields may or may not be populated, based on the [ExecuteSqlRequest.q uery_mode][google.spanner.v1.ExecuteSqlRequest.query_mode].

metadata

Field google.spanner.v1.ResultSet.metadata

rows

Field google.spanner.v1.ResultSet.rows

stats

Field google.spanner.v1.ResultSet.stats

class google.cloud.spanner_v1.types.ResultSetMetadata#

Metadata about a [ResultSet][google.spanner.v1.ResultSet] or [PartialResultSet][google.spanner.v1.PartialResultSet].

row_type#

Indicates the field names and types for the rows in the result set. For example, a SQL query like "SELECT UserId, UserName FROM Users" could return a row_type value like: :: “fields”: [ { “name”: “UserId”, “type”: { “code”: “INT64” } }, { “name”: “UserName”, “type”: { “code”: “STRING” } }, ]

transaction#

If the read or SQL query began a transaction as a side-effect, the information about the new transaction is yielded here.

row_type

Field google.spanner.v1.ResultSetMetadata.row_type

transaction

Field google.spanner.v1.ResultSetMetadata.transaction

class google.cloud.spanner_v1.types.ResultSetStats#

Additional statistics about a [ResultSet][google.spanner.v1.ResultSet] or [PartialResultSet][google.spanner.v1.PartialResultSet].

query_plan#

[QueryPlan][google.spanner.v1.QueryPlan] for the query associated with this result.

query_stats#

Aggregated statistics from the execution of the query. Only present when the query is profiled. For example, a query could return the statistics as follows: :: { “rows_returned”: “3”, “elapsed_time”: “1.22 secs”, “cpu_time”: “1.19 secs” }

row_count#

The number of rows modified by the DML statement.

row_count_exact#

Standard DML returns an exact count of rows that were modified.

row_count_lower_bound#

Partitioned DML does not offer exactly-once semantics, so it returns a lower bound of the rows modified.

query_plan

Field google.spanner.v1.ResultSetStats.query_plan

query_stats

Field google.spanner.v1.ResultSetStats.query_stats

row_count_exact

Field google.spanner.v1.ResultSetStats.row_count_exact

row_count_lower_bound

Field google.spanner.v1.ResultSetStats.row_count_lower_bound

class google.cloud.spanner_v1.types.RollbackRequest#

The request for [Rollback][google.spanner.v1.Spanner.Rollback].

session#

Required. The session in which the transaction to roll back is running.

transaction_id#

Required. The transaction to roll back.

session

Field google.spanner.v1.RollbackRequest.session

transaction_id

Field google.spanner.v1.RollbackRequest.transaction_id

class google.cloud.spanner_v1.types.ServiceDescriptorProto#
method#

Field google.protobuf.ServiceDescriptorProto.method

name#

Field google.protobuf.ServiceDescriptorProto.name

options#

Field google.protobuf.ServiceDescriptorProto.options

class google.cloud.spanner_v1.types.ServiceOptions#
deprecated#

Field google.protobuf.ServiceOptions.deprecated

uninterpreted_option#

Field google.protobuf.ServiceOptions.uninterpreted_option

class google.cloud.spanner_v1.types.Session#

A session in the Cloud Spanner API.

name#

The name of the session. This is always system-assigned; values provided when creating a session are ignored.

labels#

The labels for the session. - Label keys must be between 1 and 63 characters long and must conform to the following regular expression: [a-z]([-a-z0-9]*[a-z0-9])?. - Label values must be between 0 and 63 characters long and must conform to the regular expression ([a-z]([-a-z0-9]*[a-z0-9])?)?. - No more than 64 labels can be associated with a given session. See https://goo.gl/xmQnxf for more information on and examples of labels.

create_time#

Output only. The timestamp when the session is created.

approximate_last_use_time#

Output only. The approximate timestamp when the session is last used. It is typically earlier than the actual last use time.

class LabelsEntry#
key#

Field google.spanner.v1.Session.LabelsEntry.key

value#

Field google.spanner.v1.Session.LabelsEntry.value

approximate_last_use_time

Field google.spanner.v1.Session.approximate_last_use_time

create_time

Field google.spanner.v1.Session.create_time

labels

Field google.spanner.v1.Session.labels

name

Field google.spanner.v1.Session.name

class google.cloud.spanner_v1.types.SourceCodeInfo#
class Location#
leading_comments#

Field google.protobuf.SourceCodeInfo.Location.leading_comments

leading_detached_comments#

Field google.protobuf.SourceCodeInfo.Location.leading_detached_comments

path#

Field google.protobuf.SourceCodeInfo.Location.path

span#

Field google.protobuf.SourceCodeInfo.Location.span

trailing_comments#

Field google.protobuf.SourceCodeInfo.Location.trailing_comments

location#

Field google.protobuf.SourceCodeInfo.location

class google.cloud.spanner_v1.types.Struct#
class FieldsEntry#
key#

Field google.protobuf.Struct.FieldsEntry.key

value#

Field google.protobuf.Struct.FieldsEntry.value

fields#

Field google.protobuf.Struct.fields

class google.cloud.spanner_v1.types.StructType#

StructType defines the fields of a [STRUCT][google.spanner.v1.TypeCode.STRUCT] type.

fields#

The list of fields that make up this struct. Order is significant, because values of this struct type are represented as lists, where the order of field values matches the order of fields in the [StructType][google.spanner.v1.StructType]. In turn, the order of fields matches the order of columns in a read request, or the order of fields in the SELECT clause of a query.

class Field#

Message representing a single field of a struct.

name#

The name of the field. For reads, this is the column name. For SQL queries, it is the column alias (e.g., "Word" in the query "SELECT 'hello' AS Word"), or the column name (e.g., "ColName" in the query "SELECT ColName FROM Table"). Some columns might have an empty name (e.g., !”SELECT UPPER(ColName)”`). Note that a query result can contain multiple fields with the same name.

type#

The type of the field.

name

Field google.spanner.v1.StructType.Field.name

type

Field google.spanner.v1.StructType.Field.type

fields

Field google.spanner.v1.StructType.fields

class google.cloud.spanner_v1.types.Timestamp#
nanos#

Field google.protobuf.Timestamp.nanos

seconds#

Field google.protobuf.Timestamp.seconds

class google.cloud.spanner_v1.types.Transaction#

A transaction.

id#

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#

For snapshot read-only transactions, the read timestamp chosen for the transaction. Not returned by default: see [Transaction Options.ReadOnly.return_read_timestamp][google.spanner.v1.Tr ansactionOptions.ReadOnly.return_read_timestamp]. A timestamp in RFC3339 UTC “Zulu” format, accurate to nanoseconds. Example: "2014-10-02T15:01:23.045123456Z".

id

Field google.spanner.v1.Transaction.id

read_timestamp

Field google.spanner.v1.Transaction.read_timestamp

class google.cloud.spanner_v1.types.TransactionOptions#

Transactions

Each session can have at most one active transaction at a time. 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 (e.g., 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 wall 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. In that case, the commit will fail with error ABORTED.

If this behavior is undesirable, periodically executing a simple SQL query in the transaction (e.g., 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 <= 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.

mode#

Required. The type of transaction.

read_write#

Transaction may write. Authorization to begin a read-write transaction requires spanner.databases.beginOrRollbackReadWriteTransaction permission on the session resource.

partitioned_dml#

Partitioned DML transaction. Authorization to begin a Partitioned DML transaction requires spanner.databases.beginPartitionedDmlTransaction permission on the session resource.

read_only#

Transaction will not write. Authorization to begin a read- only transaction requires spanner.databases.beginReadOnlyTransaction permission on the session resource.

class PartitionedDml#

Message type to initiate a Partitioned DML transaction.

class ReadOnly#

Message type to initiate a read-only transaction.

timestamp_bound#

How to choose the timestamp for the read-only transaction.

strong#

Read at a timestamp where all previously committed transactions are visible.

min_read_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".

max_staleness#

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.

read_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".

exact_staleness#

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.

return_read_timestamp#

If true, the Cloud Spanner-selected read timestamp is included in the [Transaction][google.spanner.v1.Transaction] message that describes the transaction.

exact_staleness

Field google.spanner.v1.TransactionOptions.ReadOnly.exact_staleness

max_staleness

Field google.spanner.v1.TransactionOptions.ReadOnly.max_staleness

min_read_timestamp

Field google.spanner.v1.TransactionOptions.ReadOnly.min_read_timestamp

read_timestamp

Field google.spanner.v1.TransactionOptions.ReadOnly.read_timestamp

return_read_timestamp

Field google.spanner.v1.TransactionOptions.ReadOnly.return_read_timestamp

strong

Field google.spanner.v1.TransactionOptions.ReadOnly.strong

class ReadWrite#

Message type to initiate a read-write transaction. Currently this transaction type has no options.

partitioned_dml

Field google.spanner.v1.TransactionOptions.partitioned_dml

read_only

Field google.spanner.v1.TransactionOptions.read_only

read_write

Field google.spanner.v1.TransactionOptions.read_write

class google.cloud.spanner_v1.types.TransactionSelector#

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.

selector#

If no fields are set, the default is a single use transaction with strong concurrency.

single_use#

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.

id#

Execute the read or SQL query in a previously-started transaction.

begin#

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.ResultSetMeta data.transaction], which is a [Transaction][google.spanner.v1.Transaction].

begin

Field google.spanner.v1.TransactionSelector.begin

id

Field google.spanner.v1.TransactionSelector.id

single_use

Field google.spanner.v1.TransactionSelector.single_use

class google.cloud.spanner_v1.types.Type#

Type indicates the type of a Cloud Spanner value, as might be stored in a table cell or returned from an SQL query.

code#

Required. The [TypeCode][google.spanner.v1.TypeCode] for this type.

array_element_type#

If [code][google.spanner.v1.Type.code] == [ARRAY][google.spanner.v1.TypeCode.ARRAY], then array_element_type is the type of the array elements.

struct_type#

If [code][google.spanner.v1.Type.code] == [STRUCT][google.spanner.v1.TypeCode.STRUCT], then struct_type provides type information for the struct’s fields.

array_element_type

Field google.spanner.v1.Type.array_element_type

code

Field google.spanner.v1.Type.code

struct_type

Field google.spanner.v1.Type.struct_type

class google.cloud.spanner_v1.types.UninterpretedOption#
class NamePart#
is_extension#

Field google.protobuf.UninterpretedOption.NamePart.is_extension

name_part#

Field google.protobuf.UninterpretedOption.NamePart.name_part

aggregate_value#

Field google.protobuf.UninterpretedOption.aggregate_value

double_value#

Field google.protobuf.UninterpretedOption.double_value

identifier_value#

Field google.protobuf.UninterpretedOption.identifier_value

name#

Field google.protobuf.UninterpretedOption.name

negative_int_value#

Field google.protobuf.UninterpretedOption.negative_int_value

positive_int_value#

Field google.protobuf.UninterpretedOption.positive_int_value

string_value#

Field google.protobuf.UninterpretedOption.string_value

class google.cloud.spanner_v1.types.Value#
bool_value#

Field google.protobuf.Value.bool_value

list_value#

Field google.protobuf.Value.list_value

null_value#

Field google.protobuf.Value.null_value

number_value#

Field google.protobuf.Value.number_value

string_value#

Field google.protobuf.Value.string_value

struct_value#

Field google.protobuf.Value.struct_value