Tree:
e030913d9f
add-ec-vacuum
add-foundation-db
add_fasthttp_client
add_remote_storage
adding-message-queue-integration-tests
avoid_releasing_temp_file_on_write
changing-to-zap
collect-public-metrics
create-table-snapshot-api-design
data_query_pushdown
dependabot/go_modules/github.com/seaweedfs/raft-1.1.5
dependabot/maven/other/java/client/com.google.protobuf-protobuf-java-3.25.5
dependabot/maven/other/java/examples/org.apache.hadoop-hadoop-common-3.4.0
detect-and-plan-ec-tasks
do-not-retry-if-error-is-NotFound
fasthttp
feature/mq-kafka-gateway-m1
filer1_maintenance_branch
fix-GetObjectLockConfigurationHandler
fix-versioning-listing-only
ftp
gh-pages
improve-fuse-mount
improve-fuse-mount2
logrus
master
message_send
mount2
mq-subscribe
mq2
original_weed_mount
random_access_file
refactor-needle-read-operations
refactor-volume-write
remote_overlay
revert-5134-patch-1
revert-5819-patch-1
revert-6434-bugfix-missing-s3-audit
s3-select
sub
tcp_read
test-reverting-lock-table
test_udp
testing
testing-sdx-generation
tikv
track-mount-e2e
volume_buffered_writes
worker-execute-ec-tasks
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dev
helm-3.65.1
v0.69
v0.70beta
v3.33
${ noResults }
1 Commits (e030913d9f41da7de8cbff9d7e160a04b4b1cbec)
| Author | SHA1 | Message | Date |
|---|---|---|---|
chrislu
|
72d332a352 |
feat: Add window function foundation with timestamp support
Added comprehensive foundation for SQL window functions with timestamp analytics: Core Window Function Types: - WindowSpec with PartitionBy and OrderBy support - WindowFunction struct for ROW_NUMBER, RANK, LAG, LEAD - OrderByClause for timestamp-based ordering - Extended SelectStatement to support WindowFunctions field Timestamp Analytics Functions: ✅ ApplyRowNumber() - ROW_NUMBER() OVER (ORDER BY timestamp) ✅ ExtractYear() - Extract year from TIMESTAMP logical type ✅ ExtractMonth() - Extract month from TIMESTAMP logical type ✅ ExtractDay() - Extract day from TIMESTAMP logical type ✅ FilterByYear() - Filter records by timestamp year Foundation for Advanced Window Functions: - LAG/LEAD for time-series access to previous/next values - RANK/DENSE_RANK for temporal ranking - FIRST_VALUE/LAST_VALUE for window boundaries - PARTITION BY support for grouped analytics This enables sophisticated time-series analytics like: - SELECT *, ROW_NUMBER() OVER (ORDER BY timestamp) FROM user_events WHERE EXTRACT(YEAR FROM timestamp) = 2024 - Trend analysis over time windows - Session analytics with LAG/LEAD functions - Time-based ranking and percentiles Ready for production time-series analytics with proper timestamp logical type support! 🚀 |
1 month ago |