100 lines
3.7 KiB
Ruby
100 lines
3.7 KiB
Ruby
# frozen_string_literal: true
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module Gitlab
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module Database
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module Migrations
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class TestBatchedBackgroundRunner < BaseBackgroundRunner
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include Gitlab::Database::DynamicModelHelpers
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attr_reader :connection
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def initialize(result_dir:, connection:)
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super(result_dir: result_dir)
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@connection = connection
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end
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def jobs_by_migration_name
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Gitlab::Database::BackgroundMigration::BatchedMigration
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.executable
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.created_after(3.hours.ago) # Simple way to exclude migrations already running before migration testing
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.to_h do |migration|
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batching_strategy = migration.batch_class.new(connection: connection)
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smallest_batch_start = migration.next_min_value
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table_max_value = define_batchable_model(migration.table_name, connection: connection)
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.maximum(migration.column_name)
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largest_batch_start = table_max_value - migration.batch_size
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# variance is the portion of the batch range that we shrink between variance * 0 and variance * 1
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# to pick actual batches to sample.
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variance = largest_batch_start - smallest_batch_start
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batch_starts = uniform_fractions
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.lazy # frac varies from 0 to 1, values in smallest_batch_start..largest_batch_start
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.map { |frac| (variance * frac).to_i + smallest_batch_start }
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# Track previously run batches so that we stop sampling if a new batch would intersect an older one
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completed_batches = []
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jobs_to_sample = batch_starts
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# Stop sampling if a batch would intersect a previous batch
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.take_while { |start| completed_batches.none? { |batch| batch.cover?(start) } }
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.map do |batch_start|
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next_bounds = batching_strategy.next_batch(
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migration.table_name,
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migration.column_name,
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batch_min_value: batch_start,
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batch_size: migration.batch_size,
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job_arguments: migration.job_arguments
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)
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batch_min, batch_max = next_bounds
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job = migration.create_batched_job!(batch_min, batch_max)
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completed_batches << (batch_min..batch_max)
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job
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end
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[migration.job_class_name, jobs_to_sample]
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end
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end
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def run_job(job)
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Gitlab::Database::BackgroundMigration::BatchedMigrationWrapper.new(connection: connection).perform(job)
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end
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def uniform_fractions
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Enumerator.new do |y|
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# Generates equally distributed fractions between 0 and 1, with increasing detail as more are pulled from
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# the enumerator.
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# 0, 1 (special case)
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# 1/2
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# 1/4, 3/4
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# 1/8, 3/8, 5/8, 7/8
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# etc.
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# The pattern here is at each outer loop, the denominator multiplies by 2, and at each inner loop,
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# the numerator counts up all odd numbers 1 <= n < denominator.
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y << 0
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y << 1
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# denominators are each increasing power of 2
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denominators = (1..).lazy.map { |exponent| 2**exponent }
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denominators.each do |denominator|
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# Numerators at the current step are all odd numbers between 1 and the denominator
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numerators = (1..denominator).step(2)
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numerators.each do |numerator|
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next_frac = numerator.fdiv(denominator)
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y << next_frac
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end
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end
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end
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end
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end
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end
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end
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end
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