package google.spanner.v1
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service Spanner
spanner.proto:42Cloud Spanner API The Cloud Spanner API can be used to manage sessions and execute transactions on data stored in Cloud Spanner databases.
rpc CreateSession (, )
spanner.proto:62Creates a new session. A session can be used to perform transactions that read and/or modify data in a Cloud Spanner database. Sessions are meant to be reused for many consecutive transactions. Sessions can only execute one transaction at a time. To execute multiple concurrent read-write/write-only transactions, create multiple sessions. Note that standalone reads and queries use a transaction internally, and count toward the one transaction limit. Cloud Spanner limits the number of sessions that can exist at any given time; thus, it is a good idea to delete idle and/or unneeded sessions. Aside from explicit deletes, Cloud Spanner can delete sessions for which no operations are sent for more than an hour. If a session is deleted, requests to it return `NOT_FOUND`. Idle sessions can be kept alive by sending a trivial SQL query periodically, e.g., `"SELECT 1"`.
message
spanner.proto:284The request for [CreateSession][google.spanner.v1.Spanner.CreateSession].
string database = 1
Required. The database in which the new session is created.
optional session = 2
The session to create.
rpc BatchCreateSessions (, )
spanner.proto:73Creates multiple new sessions. This API can be used to initialize a session cache on the clients. See https://goo.gl/TgSFN2 for best practices on session cache management.
message
spanner.proto:294The request for [BatchCreateSessions][google.spanner.v1.Spanner.BatchCreateSessions].
string database = 1
Required. The database in which the new sessions are created.
optional session_template = 2
Parameters to be applied to each created session.
int32 session_count = 3
Required. The number of sessions to be created in this batch call. The API may return fewer than the requested number of sessions. If a specific number of sessions are desired, the client can make additional calls to BatchCreateSessions (adjusting [session_count][google.spanner.v1.BatchCreateSessionsRequest.session_count] as necessary).
message
spanner.proto:312The response for [BatchCreateSessions][google.spanner.v1.Spanner.BatchCreateSessions].
repeated session = 1
The freshly created sessions.
rpc GetSession (, )
spanner.proto:84Gets a session. Returns `NOT_FOUND` if the session does not exist. This is mainly useful for determining whether a session is still alive.
message
spanner.proto:343The request for [GetSession][google.spanner.v1.Spanner.GetSession].
string name = 1
Required. The name of the session to retrieve.
rpc ListSessions (, )
spanner.proto:91Lists all sessions in a given database.
message
spanner.proto:349The request for [ListSessions][google.spanner.v1.Spanner.ListSessions].
string database = 1
Required. The database in which to list sessions.
int32 page_size = 2
Number of sessions to be returned in the response. If 0 or less, defaults to the server's maximum allowed page size.
string page_token = 3
If non-empty, `page_token` should contain a [next_page_token][google.spanner.v1.ListSessionsResponse.next_page_token] from a previous [ListSessionsResponse][google.spanner.v1.ListSessionsResponse].
string filter = 4
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".
message
spanner.proto:377The response for [ListSessions][google.spanner.v1.Spanner.ListSessions].
repeated sessions = 1
The list of requested sessions.
string next_page_token = 2
`next_page_token` can be sent in a subsequent [ListSessions][google.spanner.v1.Spanner.ListSessions] call to fetch more of the matching sessions.
rpc DeleteSession (, )
spanner.proto:100Ends a session, releasing server resources associated with it. This will asynchronously trigger cancellation of any operations that are running with this session.
message
spanner.proto:388The request for [DeleteSession][google.spanner.v1.Spanner.DeleteSession].
string name = 1
Required. The name of the session to delete.
rpc ExecuteSql (, )
spanner.proto:119Executes an SQL statement, returning all results in a single reply. This method cannot be used to return a result set larger than 10 MiB; if the query yields more data than that, the query fails with a `FAILED_PRECONDITION` error. Operations inside read-write transactions might return `ABORTED`. If this occurs, the application should restart the transaction from the beginning. See [Transaction][google.spanner.v1.Transaction] for more details. Larger result sets can be fetched in streaming fashion by calling [ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql] instead.
rpc ExecuteStreamingSql (, stream )
spanner.proto:131Like [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql], except returns the result set as a stream. Unlike [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql], there is no limit on the size of the returned result set. However, no individual row in the result set can exceed 100 MiB, and no column value can exceed 10 MiB.
rpc ExecuteBatchDml (, )
spanner.proto:158Executes a batch of SQL DML statements. This method allows many statements to be run with lower latency than submitting them sequentially with [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]. Statements are executed in order, sequentially. [ExecuteBatchDmlResponse][Spanner.ExecuteBatchDmlResponse] will contain a [ResultSet][google.spanner.v1.ResultSet] for each DML statement that has successfully executed. If a statement fails, its error status will be returned as part of the [ExecuteBatchDmlResponse][Spanner.ExecuteBatchDmlResponse]. Execution will stop at the first failed statement; the remaining statements will not run. ExecuteBatchDml is expected to return an OK status with a response even if there was an error while processing one of the DML statements. Clients must inspect response.status to determine if there were any errors while processing the request. See more details in [ExecuteBatchDmlRequest][Spanner.ExecuteBatchDmlRequest] and [ExecuteBatchDmlResponse][Spanner.ExecuteBatchDmlResponse].
message
spanner.proto:491The request for [ExecuteBatchDml][google.spanner.v1.Spanner.ExecuteBatchDml]
string session = 1
Required. The session in which the DML statements should be performed.
optional transaction = 2
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.
repeated statements = 3
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.
int64 seqno = 4
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].
message
spanner.proto:570The 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.
repeated result_sets = 1
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].
optional status = 2
If all DML statements are executed successfully, status will be OK. Otherwise, the error status of the first failed statement.
rpc Read (, )
spanner.proto:180Reads rows from the database using key lookups and scans, as a simple key/value style alternative to [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]. This method cannot be used to return a result set larger than 10 MiB; if the read matches more data than that, the read fails with a `FAILED_PRECONDITION` error. Reads inside read-write transactions might return `ABORTED`. If this occurs, the application should restart the transaction from the beginning. See [Transaction][google.spanner.v1.Transaction] for more details. Larger result sets can be yielded in streaming fashion by calling [StreamingRead][google.spanner.v1.Spanner.StreamingRead] instead.
rpc StreamingRead (, stream )
spanner.proto:192Like [Read][google.spanner.v1.Spanner.Read], except returns the result set as a stream. Unlike [Read][google.spanner.v1.Spanner.Read], there is no limit on the size of the returned result set. However, no individual row in the result set can exceed 100 MiB, and no column value can exceed 10 MiB.
rpc BeginTransaction (, )
spanner.proto:204Begins a new transaction. This step can often be skipped: [Read][google.spanner.v1.Spanner.Read], [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] and [Commit][google.spanner.v1.Spanner.Commit] can begin a new transaction as a side-effect.
message
spanner.proto:786The request for [BeginTransaction][google.spanner.v1.Spanner.BeginTransaction].
string session = 1
Required. The session in which the transaction runs.
optional options = 2
Required. Options for the new transaction.
rpc Commit (, )
spanner.proto:219Commits a transaction. The request includes the mutations to be applied to rows in the database. `Commit` might return an `ABORTED` error. This can occur at any time; commonly, the cause is conflicts with concurrent transactions. However, it can also happen for a variety of other reasons. If `Commit` returns `ABORTED`, the caller should re-attempt the transaction from the beginning, re-using the same session.
message
spanner.proto:795The request for [Commit][google.spanner.v1.Spanner.Commit].
string session = 1
Required. The session in which the transaction to be committed is running.
oneof transaction
Required. The transaction in which to commit.
bytes transaction_id = 2
Commit a previously-started transaction.
single_use_transaction = 3
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.
repeated mutations = 4
The mutations to be executed when this transaction commits. All mutations are applied atomically, in the order they appear in this list.
message
spanner.proto:823The response for [Commit][google.spanner.v1.Spanner.Commit].
optional commit_timestamp = 1
The Cloud Spanner timestamp at which the transaction committed.
rpc Rollback (, )
spanner.proto:235Rolls back a transaction, releasing any locks it holds. It is a good idea to call this for any transaction that includes one or more [Read][google.spanner.v1.Spanner.Read] or [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] requests and ultimately decides not to commit. `Rollback` returns `OK` if it successfully aborts the transaction, the transaction was already aborted, or the transaction is not found. `Rollback` never returns `ABORTED`.
message
spanner.proto:829The request for [Rollback][google.spanner.v1.Spanner.Rollback].
string session = 1
Required. The session in which the transaction to roll back is running.
bytes transaction_id = 2
Required. The transaction to roll back.
rpc PartitionQuery (, )
spanner.proto:254Creates a set of partition tokens that can be used to execute a query operation in parallel. Each of the returned partition tokens can be used by [ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql] to specify a subset of the query result to read. The same session and read-only transaction must be used by the PartitionQueryRequest used to create the partition tokens and the ExecuteSqlRequests that use the partition tokens. Partition tokens become invalid when the session used to create them is deleted, is idle for too long, begins a new transaction, or becomes too old. When any of these happen, it is not possible to resume the query, and the whole operation must be restarted from the beginning.
message
spanner.proto:610The request for [PartitionQuery][google.spanner.v1.Spanner.PartitionQuery]
string session = 1
Required. The session used to create the partitions.
optional transaction = 2
Read only snapshot transactions are supported, read/write and single use transactions are not.
string sql = 3
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.
optional params = 4
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.
map<string, > param_types = 5
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.
optional partition_options = 6
Additional options that affect how many partitions are created.
rpc PartitionRead (, )
spanner.proto:275Creates a set of partition tokens that can be used to execute a read operation in parallel. Each of the returned partition tokens can be used by [StreamingRead][google.spanner.v1.Spanner.StreamingRead] to specify a subset of the read result to read. The same session and read-only transaction must be used by the PartitionReadRequest used to create the partition tokens and the ReadRequests that use the partition tokens. There are no ordering guarantees on rows returned among the returned partition tokens, or even within each individual StreamingRead call issued with a partition_token. Partition tokens become invalid when the session used to create them is deleted, is idle for too long, begins a new transaction, or becomes too old. When any of these happen, it is not possible to resume the read, and the whole operation must be restarted from the beginning.
message
spanner.proto:663The request for [PartitionRead][google.spanner.v1.Spanner.PartitionRead]
string session = 1
Required. The session used to create the partitions.
optional transaction = 2
Read only snapshot transactions are supported, read/write and single use transactions are not.
string table = 3
Required. The name of the table in the database to be read.
string index = 4
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.
repeated string columns = 5
The columns of [table][google.spanner.v1.PartitionReadRequest.table] to be returned for each row matching this request.
optional key_set = 6
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.
optional partition_options = 9
Additional options that affect how many partitions are created.
message
spanner.proto:493A single DML statement.
Used in:
string sql = 1
Required. The DML string.
optional params = 2
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.
map<string, > param_types = 3
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.
message
spanner.proto:395The request for [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] and [ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql].
Used as request type in: Spanner.ExecuteSql, Spanner.ExecuteStreamingSql
string session = 1
Required. The session in which the SQL query should be performed.
optional transaction = 2
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.
string sql = 3
Required. The SQL string.
optional params = 4
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.
map<string, > param_types = 5
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.
bytes resume_token = 6
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.
ExecuteSqlRequest.QueryMode query_mode = 7
Used to control the amount of debugging information returned in [ResultSetStats][google.spanner.v1.ResultSetStats]. If [partition_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.ExecuteSqlRequest.QueryMode.NORMAL].
bytes partition_token = 8
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.
int64 seqno = 9
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.
Mode in which the statement must be processed.
Used in:
NORMAL = 0
The default mode. Only the statement results are returned.
PLAN = 1
This mode returns only the query plan, without any results or execution statistics information.
PROFILE = 2
This mode returns both the query plan and the execution statistics along with the results.
message
keys.proto:117KeyRange 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.
Used in:
oneof start_key_type
The start key must be provided. It can be either closed or open.
start_closed = 1
If the start is closed, then the range includes all rows whose first `len(start_closed)` key columns exactly match `start_closed`.
start_open = 2
If the start is open, then the range excludes rows whose first `len(start_open)` key columns exactly match `start_open`.
oneof end_key_type
The end key must be provided. It can be either closed or open.
end_closed = 3
If the end is closed, then the range includes all rows whose first `len(end_closed)` key columns exactly match `end_closed`.
end_open = 4
If the end is open, then the range excludes rows whose first `len(end_open)` key columns exactly match `end_open`.
message
keys.proto:148`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.
Used in: , ,
repeated keys = 1
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].
repeated ranges = 2
A list of key ranges. See [KeyRange][google.spanner.v1.KeyRange] for more information about key range specifications.
bool all = 3
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.
message
mutation.proto:33A 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.
Used in:
oneof operation
Required. The operation to perform.
insert = 1
Insert new rows in a table. If any of the rows already exist, the write or transaction fails with error `ALREADY_EXISTS`.
update = 2
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 = 3
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 = 4
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_update][google.spanner.v1.Mutation.insert_or_update], this means any values not explicitly written become `NULL`.
delete = 5
Delete rows from a table. Succeeds whether or not the named rows were present.
message
mutation.proto:64Arguments to [delete][google.spanner.v1.Mutation.delete] operations.
Used in:
string table = 1
Required. The table whose rows will be deleted.
optional key_set = 2
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.
message
mutation.proto:38Arguments 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.
Used in:
string table = 1
Required. The table whose rows will be written.
repeated string columns = 2
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.
repeated values = 3
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 `Mutation`s, 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].
message
result_set.proto:61Partial 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.
Used as response type in: Spanner.ExecuteStreamingSql, Spanner.StreamingRead
optional metadata = 1
Metadata about the result set, such as row type information. Only present in the first response.
repeated values = 2
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.StructType.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 `PartialResultSet`s 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 `PartialResultSet`s encodes two rows, one containing the field value `"Hello"`, and a second containing the field value `"World" = "W" + "orl" + "d"`.
bool chunked_value = 3
If true, then the final value in [values][google.spanner.v1.PartialResultSet.values] is chunked, and must be combined with more values from subsequent `PartialResultSet`s to obtain a complete field value.
bytes resume_token = 4
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.
optional stats = 5
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.ExecuteSqlRequest.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.
message
spanner.proto:704Information returned for each partition returned in a PartitionResponse.
Used in:
bytes partition_token = 1
This token can be passed to Read, StreamingRead, ExecuteSql, or ExecuteStreamingSql requests to restrict the results to those identified by this partition token.
message
spanner.proto:589Options for a PartitionQueryRequest and PartitionReadRequest.
Used in: ,
int64 partition_size_bytes = 1
**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.
int64 max_partitions = 2
**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.
message
spanner.proto:713The response for [PartitionQuery][google.spanner.v1.Spanner.PartitionQuery] or [PartitionRead][google.spanner.v1.Spanner.PartitionRead]
Used as response type in: Spanner.PartitionQuery, Spanner.PartitionRead
repeated partitions = 1
Partitions created by this request.
optional transaction = 2
Transaction created by this request.
message
query_plan.proto:31Node information for nodes appearing in a [QueryPlan.plan_nodes][google.spanner.v1.QueryPlan.plan_nodes].
Used in:
int32 index = 1
The `PlanNode`'s index in [node list][google.spanner.v1.QueryPlan.plan_nodes].
PlanNode.Kind kind = 2
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.
string display_name = 3
The display name for the node.
repeated child_links = 4
List of child node `index`es and their relationship to this parent.
optional short_representation = 5
Condensed representation for [SCALAR][google.spanner.v1.PlanNode.Kind.SCALAR] nodes.
optional metadata = 6
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" }
optional execution_stats = 7
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.
message
query_plan.proto:34Metadata associated with a parent-child relationship appearing in a [PlanNode][google.spanner.v1.PlanNode].
Used in:
int32 child_index = 1
The node to which the link points.
string type = 2
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.
string variable = 3
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.
The kind of [PlanNode][google.spanner.v1.PlanNode]. Distinguishes between the two different kinds of nodes that can appear in a query plan.
Used in:
KIND_UNSPECIFIED = 0
Not specified.
RELATIONAL = 1
Denotes a Relational operator node in the expression tree. Relational operators represent iterative processing of rows during query execution. For example, a `TableScan` operation that reads rows from a table.
SCALAR = 2
Denotes a Scalar node in the expression tree. Scalar nodes represent non-iterable entities in the query plan. For example, constants or arithmetic operators appearing inside predicate expressions or references to column names.
message
query_plan.proto:57Condensed representation of a node and its subtree. Only present for `SCALAR` [PlanNode(s)][google.spanner.v1.PlanNode].
Used in:
string description = 1
A string representation of the expression subtree rooted at this node.
map<string, int32> subqueries = 2
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.
message
query_plan.proto:126Contains an ordered list of nodes appearing in the query plan.
Used in:
repeated plan_nodes = 1
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`.
message
spanner.proto:723The request for [Read][google.spanner.v1.Spanner.Read] and [StreamingRead][google.spanner.v1.Spanner.StreamingRead].
Used as request type in: Spanner.Read, Spanner.StreamingRead
string session = 1
Required. The session in which the read should be performed.
optional transaction = 2
The transaction to use. If none is provided, the default is a temporary read-only transaction with strong concurrency.
string table = 3
Required. The name of the table in the database to be read.
string index = 4
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.
repeated string columns = 5
The columns of [table][google.spanner.v1.ReadRequest.table] to be returned for each row matching this request.
optional key_set = 6
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 [partition_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.
int64 limit = 8
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.
bytes resume_token = 9
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.
bytes partition_token = 10
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.
message
result_set.proto:35Results from [Read][google.spanner.v1.Spanner.Read] or [ExecuteSql][google.spanner.v1.Spanner.ExecuteSql].
Used as response type in: Spanner.ExecuteSql, Spanner.Read
Used as field type in:
optional metadata = 1
Metadata about the result set, such as row type information.
repeated rows = 2
Each element in `rows` is a row whose format is defined by [metadata.row_type][google.spanner.v1.ResultSetMetadata.row_type]. The ith element in each row matches the ith field in [metadata.row_type][google.spanner.v1.ResultSetMetadata.row_type]. Elements are encoded based on type as described [here][google.spanner.v1.TypeCode].
optional stats = 3
Query plan and execution statistics for the SQL statement that produced this result set. These can be requested by setting [ExecuteSqlRequest.query_mode][google.spanner.v1.ExecuteSqlRequest.query_mode]. DML statements always produce stats containing the number of rows modified, unless executed using the [ExecuteSqlRequest.QueryMode.PLAN][google.spanner.v1.ExecuteSqlRequest.QueryMode.PLAN] [ExecuteSqlRequest.query_mode][google.spanner.v1.ExecuteSqlRequest.query_mode]. Other fields may or may not be populated, based on the [ExecuteSqlRequest.query_mode][google.spanner.v1.ExecuteSqlRequest.query_mode].
message
result_set.proto:165Metadata about a [ResultSet][google.spanner.v1.ResultSet] or [PartialResultSet][google.spanner.v1.PartialResultSet].
Used in: ,
optional row_type = 1
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" } }, ]
optional transaction = 2
If the read or SQL query began a transaction as a side-effect, the information about the new transaction is yielded here.
message
result_set.proto:183Additional statistics about a [ResultSet][google.spanner.v1.ResultSet] or [PartialResultSet][google.spanner.v1.PartialResultSet].
Used in: ,
optional query_plan = 1
[QueryPlan][google.spanner.v1.QueryPlan] for the query associated with this result.
optional query_stats = 2
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" }
oneof row_count
The number of rows modified by the DML statement.
int64 row_count_exact = 3
Standard DML returns an exact count of rows that were modified.
int64 row_count_lower_bound = 4
Partitioned DML does not offer exactly-once semantics, so it returns a lower bound of the rows modified.
message
spanner.proto:318A session in the Cloud Spanner API.
Used as response type in: Spanner.CreateSession, Spanner.GetSession
Used as field type in: , , ,
string name = 1
The name of the session. This is always system-assigned; values provided when creating a session are ignored.
map<string, string> labels = 2
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.
optional create_time = 3
Output only. The timestamp when the session is created.
optional approximate_last_use_time = 4
Output only. The approximate timestamp when the session is last used. It is typically earlier than the actual last use time.
message
type.proto:47`StructType` defines the fields of a [STRUCT][google.spanner.v1.TypeCode.STRUCT] type.
Used in: ,
repeated fields = 1
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.
message
type.proto:49Message representing a single field of a struct.
Used in:
string name = 1
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.
optional type = 2
The type of the field.
message
transaction.proto:415A transaction.
Used as response type in: Spanner.BeginTransaction
Used as field type in: ,
bytes id = 1
`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.
optional read_timestamp = 2
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"`.
message
transaction.proto:312# 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.
Used in: , ,
oneof mode
Required. The type of transaction.
read_write = 1
Transaction may write. Authorization to begin a read-write transaction requires `spanner.databases.beginOrRollbackReadWriteTransaction` permission on the `session` resource.
partitioned_dml = 3
Partitioned DML transaction. Authorization to begin a Partitioned DML transaction requires `spanner.databases.beginPartitionedDmlTransaction` permission on the `session` resource.
read_only = 2
Transaction will not write. Authorization to begin a read-only transaction requires `spanner.databases.beginReadOnlyTransaction` permission on the `session` resource.
message
transaction.proto:318Message type to initiate a Partitioned DML transaction.
Used in:
(message has no fields)
message
transaction.proto:321Message type to initiate a read-only transaction.
Used in:
oneof timestamp_bound
How to choose the timestamp for the read-only transaction.
bool strong = 1
Read at a timestamp where all previously committed transactions are visible.
min_read_timestamp = 2
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 = 3
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 = 4
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 = 5
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`.
bool return_read_timestamp = 6
If true, the Cloud Spanner-selected read timestamp is included in the [Transaction][google.spanner.v1.Transaction] message that describes the transaction.
message
transaction.proto:315Message type to initiate a read-write transaction. Currently this transaction type has no options.
Used in:
(message has no fields)
message
transaction.proto:441This 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.
Used in: , , , ,
oneof selector
If no fields are set, the default is a single use transaction with strong concurrency.
single_use = 1
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.
bytes id = 2
Execute the read or SQL query in a previously-started transaction.
begin = 3
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].
message
type.proto:30`Type` indicates the type of a Cloud Spanner value, as might be stored in a table cell or returned from an SQL query.
Used in: , , ,
TypeCode code = 1
Required. The [TypeCode][google.spanner.v1.TypeCode] for this type.
optional array_element_type = 2
If [code][google.spanner.v1.Type.code] == [ARRAY][google.spanner.v1.TypeCode.ARRAY], then `array_element_type` is the type of the array elements.
optional struct_type = 3
If [code][google.spanner.v1.Type.code] == [STRUCT][google.spanner.v1.TypeCode.STRUCT], then `struct_type` provides type information for the struct's fields.
`TypeCode` is used as part of [Type][google.spanner.v1.Type] to indicate the type of a Cloud Spanner value. Each legal value of a type can be encoded to or decoded from a JSON value, using the encodings described below. All Cloud Spanner values can be `null`, regardless of type; `null`s are always encoded as a JSON `null`.
Used in:
TYPE_CODE_UNSPECIFIED = 0
Not specified.
BOOL = 1
Encoded as JSON `true` or `false`.
INT64 = 2
Encoded as `string`, in decimal format.
FLOAT64 = 3
Encoded as `number`, or the strings `"NaN"`, `"Infinity"`, or `"-Infinity"`.
TIMESTAMP = 4
Encoded as `string` in RFC 3339 timestamp format. The time zone must be present, and must be `"Z"`. If the schema has the column option `allow_commit_timestamp=true`, the placeholder string `"spanner.commit_timestamp()"` can be used to instruct the system to insert the commit timestamp associated with the transaction commit.
DATE = 5
Encoded as `string` in RFC 3339 date format.
STRING = 6
Encoded as `string`.
BYTES = 7
Encoded as a base64-encoded `string`, as described in RFC 4648, section 4.
ARRAY = 8
Encoded as `list`, where the list elements are represented according to [array_element_type][google.spanner.v1.Type.array_element_type].
STRUCT = 9
Encoded as `list`, where list element `i` is represented according to [struct_type.fields[i]][google.spanner.v1.StructType.fields].