feat: add exponential backoff retry strategy
Introduce a retry policy with exponential backoff and jitter for extractor and loader errors, with configurable max attempts and delay caps.
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@@ -9,18 +9,21 @@ import (
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type RetryConfig struct {
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Attempts int `yaml:"attempts"`
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BaseDelayMs int `yaml:"base_delay_ms"`
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MaxDelayMs int `yaml:"max_delay_ms"`
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MaxJitterMs int `yaml:"max_jitter_ms"`
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}
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type JobConfig struct {
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MaxExtractors int `yaml:"max_extractors"`
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MaxLoaders int `yaml:"max_loaders"`
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QueueSize int `yaml:"queue_size"`
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ChunkSize int `yaml:"chunk_size"`
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ChunksPerBatch int `yaml:"chunks_per_batch"`
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RowsPerBatch int64
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TruncateTarget bool `yaml:"truncate_target"`
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TruncateMethod string `yaml:"truncate_method"`
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Retry RetryConfig `yaml:"retry"`
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MaxExtractors int `yaml:"max_extractors"`
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MaxLoaders int `yaml:"max_loaders"`
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QueueSize int `yaml:"queue_size"`
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BatchSize int `yaml:"batch_size"`
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BatchesPerPartition int `yaml:"batches_per_partition"`
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TruncateTarget bool `yaml:"truncate_target"`
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TruncateMethod string `yaml:"truncate_method"`
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Retry RetryConfig `yaml:"retry"`
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RowsPerPartition int64
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}
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type TableInfo struct {
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@@ -71,7 +74,7 @@ func (c *MigrationConfig) UnmarshalYAML(value *yaml.Node) error {
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c.MaxParallelWorkers = raw.MaxParallelWorkers
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c.Defaults = raw.Defaults
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c.Defaults.RowsPerBatch = int64(raw.Defaults.ChunkSize * raw.Defaults.ChunksPerBatch)
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c.Defaults.RowsPerPartition = int64(raw.Defaults.BatchSize * raw.Defaults.BatchesPerPartition)
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for _, node := range raw.Jobs {
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job := Job{
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@@ -82,7 +85,7 @@ func (c *MigrationConfig) UnmarshalYAML(value *yaml.Node) error {
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return err
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}
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job.RowsPerBatch = int64(job.ChunkSize * job.ChunksPerBatch)
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job.RowsPerPartition = int64(job.BatchSize * job.BatchesPerPartition)
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c.Jobs = append(c.Jobs, job)
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}
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