Typorithm learning path
Databases & Data
Type the data layer — ClickHouse, MongoDB, InfluxDB, Redis, and Spark.
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Unit 1 · 3 topics
Columns & Engines
Columnar storage and the MergeTree engine — table creation, column types and codecs, parts and merges.
Unit 2 · 4 topics
Indexing & Partitioning
Sparse primary index and granules, partition pruning, data-skipping indexes, and PREWHERE.
Unit 3 · 4 topics
Aggregation & Views
Summing and aggregating MergeTree engines, materialized views, and ReplacingMergeTree dedup.
Unit 4 · 4 topics
Querying
Aggregate functions, arrayJoin, window functions, and SAMPLE for fast approximate analytics.
Unit 5 · 4 topics
Scale & Ops
Distributed sharding, ReplicatedMergeTree, TTL lifecycle, and per-column compression codecs.
Unit 6 · 3 topics
mongosh
Connect and navigate, manage databases and collections, and import/export data with mongosh.
Unit 7 · 4 topics
CRUD
insertOne/insertMany, find/findOne, updateOne/updateMany with $set, and scoped deletes.
Unit 8 · 3 topics
Query Operators
Comparison and logical operators, existence checks, projection, sorting, and pagination.
Unit 9 · 3 topics
Aggregation
The pipeline — $match, $group accumulators, $project, $sort, $lookup joins, and $unwind.
Unit 10 · 3 topics
Indexes
Single and compound indexes, explain() plans, and text, TTL, and unique indexes.
Unit 11 · 3 topics
Line Protocol
The write format, the influx write CLI, and batching with the tag-vs-field design choice.
Unit 12 · 3 topics
Flux
Pipe-forward queries — from/range/filter, aggregateWindow downsampling, and group/pivot.
Unit 13 · 3 topics
Buckets & InfluxQL
Buckets and retention, the InfluxQL SQL dialect, and running Flux from the influx CLI.
Unit 14 · 3 topics
DataFrames
Read and inspect data, select and filter columns, and derive columns with withColumn.
Unit 15 · 3 topics
Transformations & Actions
groupBy/agg, the lazy transformation-vs-action model and DAG, and cache/persist.
Unit 16 · 3 topics
Spark SQL
Temp views and SQL, window functions, and distributed joins with the broadcast hint.
Unit 17 · 3 topics
Strings & Keys
SET/GET with TTL, atomic INCR counters, and key namespacing with SCAN — the Redis string foundation.
Unit 18 · 3 topics
Data Types
Lists as queues, hashes as objects, and sorted sets as leaderboards — Redis's core collections.
Unit 19 · 3 topics
Patterns
Cache-aside with TTLs, pub/sub messaging, and the SET NX distributed lock.
Unit 20 · 3 topics
Persistence & Scale
RDB snapshots vs AOF logging, replication and failover, and cluster hash-slot sharding.