How should I store a tick before sending it for analysis? - briefly
Store each tick in a thread‑safe, fixed‑size buffer (e.g., a ring queue) and serialize it to a compact binary format such as Protocol Buffers, optionally compressing before transmission. Persist the buffer to durable storage only if network delivery fails, preserving order and timestamps.
How should I store a tick before sending it for analysis? - in detail
When a single market event is captured, the data must be preserved in a form that guarantees accuracy, durability, and efficient transfer.
First, define the data structure. Include fields such as instrument identifier, exact timestamp (nanosecond resolution if available), price, size, exchange code, and any relevant flags. Use a fixed‑size binary layout (e.g., Protocol Buffers, FlatBuffers, or a custom struct) to avoid variable‑length overhead and to simplify deserialization on the receiving side.
Second, apply immediate validation. Verify that the timestamp is monotonic relative to the previous event for the same instrument, that price and size are within expected ranges, and that required fields are non‑null. Reject or flag any record that fails these checks before it is stored.
Third, choose a storage medium that matches the required latency and durability. For short‑term buffering, place the record in an in‑memory ring buffer or lock‑free queue. Persist the same record to a fast write‑ahead log on SSD, using append‑only mode to guarantee crash recovery. Ensure the log file is flushed (fsync) at intervals that balance throughput and data loss risk.
Fourth, compress the data only after it has been written to the durable log. Apply a lightweight, fast algorithm such as LZ4 or Zstandard at a moderate compression level. Store the compressed chunk alongside an index that maps timestamps to file offsets, enabling rapid retrieval for later analysis.
Fifth, manage concurrency. Protect the in‑memory buffer with atomic operations or a concurrent queue implementation. Use separate threads for ingestion, validation, persistence, and compression to prevent bottlenecks. Each thread should communicate through thread‑safe queues, avoiding shared mutable state.
Sixth, prepare the payload for transmission. Serialize the compressed block into a network‑friendly format (e.g., MessagePack or a length‑prefixed binary frame). Attach a checksum (e.g., CRC32C) and a sequence identifier to detect corruption and ordering issues on the receiver side.
Seventh, implement error handling. If the network send fails, retry using exponential back‑off while preserving the original order. After a configurable number of attempts, move the payload to a dead‑letter queue for manual inspection.
Finally, monitor key metrics: ingestion latency, buffer occupancy, disk write latency, compression ratio, and transmission success rate. Export these metrics to a monitoring system to allow proactive tuning of buffer sizes, compression settings, and retry policies.
By following this sequence—structured binary representation, immediate validation, dual buffering (memory and durable log), fast compression, thread‑isolated pipelines, robust serialization, and disciplined error recovery—the tick can be stored reliably and transmitted efficiently for downstream analysis.