mhtirogla
Home
Systems
API
Pricing
About
Log in
← Back
Home
›
Systems
›
Data processing and pipelines
sql-transform
SQL transformation layer
dbt
System
Techniques · 4
Primitives · 18
sql-transform
Column level lineage
storage · medium: Derive which source columns feed each output column by analysing SQL plans
Incremental view maintenance
storage · medium: Update materialized views from deltas instead of recomputing
Change data capture
storage · medium: Decode the database's own commit log into row-change events in commit order, with a resume position, so any consumer can mirror the data exactly.
›
Incremental sync cursors
distributed · medium: The client keeps one opaque token; each pull returns only the changes after it plus the next token, so sync cost scales with what changed, not with the dataset.
›
Recursive-descent parsing
compilers · low: Hand-written top-down parser with one function per grammar rule; simple, fast, with full control over error messages and recovery.
›
Topological sort
graphs · low: Order the vertices of a DAG so every edge points forward; the core of build systems, schedulers and dependency resolution, with cycle detection for free.
›
Slowly changing dimensions
storage · low: SCD type 1/2 history tables with validity ranges
Upsert merge
storage · low: MERGE/upsert by key with deduplication and late-arriving data rules
Name resolution
compilers · low: Bind every use of a name to its declaration with a scope stack, handling shadowing, hoisting and closure capture in one AST walk.
›
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Relational algebra
storage · low: Relational operators and equivalence rules: selection pushdown, join reordering, projections
Hash aggregation
storage · low: GROUP BY via hash tables with partitioning and spill to disk
Consumer offsets
distributed · low: Each consumer group stores one integer per partition, the next position to read, so a restarted consumer resumes where it left off with at-least-once delivery.
›
Message sequence numbers
distributed · low: A per-stream counter on every message lets the receiver detect loss, duplicates and reordering, ack cheaply and resume after reconnect with "send from N".
›
Write-ahead log
storage · low: Append each change to a checksummed sequential log and fsync it before touching data pages; the basis of crash durability in nearly every database.
›
Cursor pagination
networking · low: Keyset/opaque-cursor pagination for stable incremental reads from APIs and tables
Fencing tokens
distributed · low: A number that grows with every lock grant and is checked by the protected resource, so a paused ex-holder's late write is rejected.
›
Segmented log
distributed · low: Split an append-only log into files named by their first offset, write only the newest, and find any record by binary search plus a sparse index.
›
CRC32C checksums
hardware-os · low: The Castagnoli CRC-32 with dedicated instructions on x86 (SSE4.2) and ARMv8. It is the standard fast integrity check for storage blocks, logs and network frames.
›
fsync, O_DSYNC and O_DIRECT
hardware-os · low: What fsync, fdatasync, O_DSYNC, O_DIRECT and F_FULLFSYNC really guarantee on Linux and macOS, and the exact call sequences for crash-safe files.
›
+ 2 more primitives
System
Techniques · 4
Primitives · 18
sql-transform
Column level lineage
storage · medium: Derive which source columns feed each output column by analysing SQL plans
Incremental view maintenance
storage · medium: Update materialized views from deltas instead of recomputing
Change data capture
storage · medium: Decode the database's own commit log into row-change events in commit order, with a resume position, so any consumer can mirror the data exactly.
›
Incremental sync cursors
distributed · medium: The client keeps one opaque token; each pull returns only the changes after it plus the next token, so sync cost scales with what changed, not with the dataset.
›
Recursive-descent parsing
compilers · low: Hand-written top-down parser with one function per grammar rule; simple, fast, with full control over error messages and recovery.
›
Topological sort
graphs · low: Order the vertices of a DAG so every edge points forward; the core of build systems, schedulers and dependency resolution, with cycle detection for free.
›
Slowly changing dimensions
storage · low: SCD type 1/2 history tables with validity ranges
Upsert merge
storage · low: MERGE/upsert by key with deduplication and late-arriving data rules
Name resolution
compilers · low: Bind every use of a name to its declaration with a scope stack, handling shadowing, hoisting and closure capture in one AST walk.
›
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Relational algebra
storage · low: Relational operators and equivalence rules: selection pushdown, join reordering, projections
Hash aggregation
storage · low: GROUP BY via hash tables with partitioning and spill to disk
Consumer offsets
distributed · low: Each consumer group stores one integer per partition, the next position to read, so a restarted consumer resumes where it left off with at-least-once delivery.
›
Message sequence numbers
distributed · low: A per-stream counter on every message lets the receiver detect loss, duplicates and reordering, ack cheaply and resume after reconnect with "send from N".
›
Write-ahead log
storage · low: Append each change to a checksummed sequential log and fsync it before touching data pages; the basis of crash durability in nearly every database.
›
Cursor pagination
networking · low: Keyset/opaque-cursor pagination for stable incremental reads from APIs and tables
Fencing tokens
distributed · low: A number that grows with every lock grant and is checked by the protected resource, so a paused ex-holder's late write is rejected.
›
Segmented log
distributed · low: Split an append-only log into files named by their first offset, write only the newest, and find any record by binary search plus a sparse index.
›
CRC32C checksums
hardware-os · low: The Castagnoli CRC-32 with dedicated instructions on x86 (SSE4.2) and ARMv8. It is the standard fast integrity check for storage blocks, logs and network frames.
›
fsync, O_DSYNC and O_DIRECT
hardware-os · low: What fsync, fdatasync, O_DSYNC, O_DIRECT and F_FULLFSYNC really guarantee on Linux and macOS, and the exact call sequences for crash-safe files.
›
SIMD programming
hardware-os · low: Process 4-16 lanes per instruction with AVX2, AVX-512 or NEON via Rust std::arch, with runtime dispatch and a portable fallback.
›
Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
Copy for AI
Similar systems
Share the most building blocks with this one.
data-catalog
18 %