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https://issues.apache.org/jira/browse/BEAM-7246?focusedWorklogId=381710&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-381710
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ASF GitHub Bot logged work on BEAM-7246:
----------------------------------------
Author: ASF GitHub Bot
Created on: 04/Feb/20 16:54
Start Date: 04/Feb/20 16:54
Worklog Time Spent: 10m
Work Description: nielm commented on pull request #10712: [BEAM-7246]
Added Google Spanner Write Transform
URL: https://github.com/apache/beam/pull/10712#discussion_r374795643
##########
File path: sdks/python/apache_beam/io/gcp/experimental/spannerio.py
##########
@@ -109,20 +111,74 @@
ReadFromSpanner takes this transform in the constructor and pass this to the
read pipeline as the singleton side input.
+
+Writing Data to Cloud Spanner.
+
+The WriteToSpanner transform writes to Cloud Spanner by executing a
+collection a input rows (WriteMutation). The mutations are grouped into
+batches for efficiency.
+
+WriteToSpanner transform relies on the WriteMutation objects which is exposed
+by the SpannerIO API. WriteMutation have five static methods (insert, update,
+insert_or_update, replace, delete). These methods returns the instance of the
+_Mutator object which contains the mutation type and the Spanner Mutation
+object. For more details, review the docs of the class SpannerIO.WriteMutation.
+For example:::
+
+ mutations = [
+ WriteMutation.insert(table='user', columns=('name', 'email'),
+ values=[('sara'. 's...@dev.com')])
+ ]
+ _ = (p
+ | beam.Create(mutations)
+ | WriteToSpanner(
+ project_id=SPANNER_PROJECT_ID,
+ instance_id=SPANNER_INSTANCE_ID,
+ database_id=SPANNER_DATABASE_NAME)
+ )
+
+You can also create WriteMutation via calling its constructor. For example:::
+
+ mutations = [
+ WriteMutation(insert='users', columns=('name', 'email'),
+ values=[('sara", 's...@example.com')])
+ ]
+
+For more information, review the docs available on WriteMutation class.
+
+WriteToSpanner transform also takes 'max_batch_size_bytes' param which is set
+to 1MB (1048576 bytes) by default. This parameter used to reduce the number of
Review comment:
There is one other batching parameter which is important -- the maximum
number of cells being mutated. Spanner has a hard 20K limit here, so a batch
must have less than 20K mutated cells, including cells being mutated in
indexes.
Java version sets this to 5K by default.
A third parameter max_number_rows was also added recently to java, limiting
the total number of rows in a batch.
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Issue Time Tracking
-------------------
Worklog Id: (was: 381710)
Time Spent: 15h 50m (was: 15h 40m)
> Create a Spanner IO for Python
> ------------------------------
>
> Key: BEAM-7246
> URL: https://issues.apache.org/jira/browse/BEAM-7246
> Project: Beam
> Issue Type: Bug
> Components: io-py-gcp
> Reporter: Reuven Lax
> Assignee: Shehzaad Nakhoda
> Priority: Major
> Time Spent: 15h 50m
> Remaining Estimate: 0h
>
> Add I/O support for Google Cloud Spanner for the Python SDK (Batch Only).
> Testing in this work item will be in the form of DirectRunner tests and
> manual testing.
> Integration and performance tests are a separate work item (not included
> here).
> See https://beam.apache.org/documentation/io/built-in/. The goal is to add
> Google Clound Spanner to the Database column for the Python/Batch row.
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