{"id":19273595,"url":"https://github.com/zikwall/clickhouse-buffer","last_synced_at":"2025-04-21T22:33:05.686Z","repository":{"id":37087446,"uuid":"378092189","full_name":"zikwall/clickhouse-buffer","owner":"zikwall","description":"Native Go, fast and easy-to-use writer for asynchronous streaming batches to ClickHouse. 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Asynchronous write client is recommended for frequent periodic writes.\n- [x] **blocking.**\n\n**Client buffer engines:**\n\n- [x] **in-memory** - use native channels and slices\n- [x] **redis** - use redis server as queue and buffer\n- [x] **in-memory-sync** - if you get direct access to buffer, it will help to avoid data race\n- [x] **retries** - resending \"broken\" or for some reason not sent packets\n\n### Usage\n\n```go\nimport (\n    \"database/sql\"\n\n    \"github.com/zikwall/clickhouse-buffer/v4/src/cx\"\n    \"github.com/zikwall/clickhouse-buffer/v4/src/db/cxnative\"\n    \"github.com/zikwall/clickhouse-buffer/v4/src/db/cxsql\"\n)\n\n// if you already have a connection to Clickhouse you can just use wrappers\n// with native interface\nch := cxnative.NewClickhouseWithConn(driver.Conn, \u0026cx.RuntimeOptions{})\n// or use database/sql interface\nch := cxsql.NewClickhouseWithConn(*sql.DB, \u0026cx.RuntimeOptions{})\n```\n\n```go\n// if you don't want to create connections yourself, \n// package can do it for you, just call the connection option you need:\n\n// with native interface\nch, conn, err := cxnative.NewClickhouse(ctx, \u0026clickhouse.Options{\n    Addr: ctx.StringSlice(\"clickhouse-host\"),\n        Auth: clickhouse.Auth{\n        Database:  ctx.String(\"clickhouse-database\"),\n        Username:  ctx.String(\"clickhouse-username\"),\n        Password:  ctx.String(\"clickhouse-password\"),\n    },\n    Settings: clickhouse.Settings{\n        \"max_execution_time\": 60,\n    },\n    DialTimeout: 5 * time.Second,\n    Compression: \u0026clickhouse.Compression{\n        Method: clickhouse.CompressionLZ4,\n    },\n    Debug: ctx.Bool(\"debug\"),\n}, \u0026cx.RuntimeOptions{})\n\n// or with database/sql interface\nch, conn, err := cxsql.NewClickhouse(ctx, \u0026clickhouse.Options{\n    Addr: ctx.StringSlice(\"clickhouse-host\"),\n        Auth: clickhouse.Auth{\n        Database:  ctx.String(\"clickhouse-database\"),\n        Username:  ctx.String(\"clickhouse-username\"),\n        Password:  ctx.String(\"clickhouse-password\"),\n    },\n    Settings: clickhouse.Settings{\n        \"max_execution_time\": 60,\n    },\n    DialTimeout: 5 * time.Second,\n    Compression: \u0026clickhouse.Compression{\n        Method: clickhouse.CompressionLZ4,\n    },\n    Debug: ctx.Bool(\"debug\"),\n}, \u0026cx.RuntimeOptions{})\n```\n\n#### Create main data streamer client and write data\n\n```go\nimport (\n    clickhousebuffer \"github.com/zikwall/clickhouse-buffer/v4\"\n    \"github.com/zikwall/clickhouse-buffer/v4/src/buffer/cxmem\"\n    \"github.com/zikwall/clickhouse-buffer/v4/src/db/cxnative\"\n)\n// create root client\nclient := clickhousebuffer.NewClientWithOptions(ctx, ch, clickhousebuffer.NewOptions(\n    clickhousebuffer.WithFlushInterval(2000),\n    clickhousebuffer.WithBatchSize(5000),\n    clickhousebuffer.WithDebugMode(true),\n    clickhousebuffer.WithRetry(true),\n))\n// create buffer engine\nbuffer := cxmem.NewBuffer(\n    client.Options().BatchSize(),\n)\n// or use redis\nbuffer := cxredis.NewBuffer(\n    ctx, *redis.Client, \"bucket\", client.Options().BatchSize(),\n)\n// create new writer api: table name with columns\nwriteAPI := client.Writer(\n    ctx, \n    // order of the values  []string{\"id\", \"uuid\", \"insert_ts\"}\n    // must correspond to the return values in the (*MyTable).Row() method, which will be shown below\n    cx.NewView(\"clickhouse_database.my_table\", []string{\"id\", \"uuid\", \"insert_ts\"}),\n    buffer,\n)\n\n// define your custom data structure\ntype MyTable struct {\n    id       int\n    uuid     string\n    insertTS time.Time\n}\n// the structure above is a reflection of the entity-table in the database\n// CREATE TABLE IF NOT EXISTS MyTable (\n//  id        \tInt32,\n//  uuid        String,\n//  insert_ts   String\n// ) engine=Memory\n\n// and implement cx.Vectorable interface\n// (*MyTable).Row() method describes how will the data be written to the table and in what order\n// similar to the INSERT INTO (id, uuid, insert_ts) VALUES (...), (...), (...) query\n// the order of return must correspond to the scheme described above: []string{\"id\", \"uuid\", \"insert_ts\"}\nfunc (t *MyTable) Row() cx.Vector {\n    return cx.Vector{\n        t.id,\n        t.uuid,\n        t.insertTS.Format(time.RFC822),\n    }\n}\n\n// async write your data\nwriteAPI.WriteRow(\u0026MyTable{\n    id: 1, uuid: \"1\", insertTS: time.Now(),\n})\n// or use a safe way (same as WriteRow, but safer)\nwriteAPI.TryWriteRow(\u0026MyTable{\n    id: 1, uuid: \"1\", insertTS: time.Now(),\n})\n// or faster\nwriteAPI.WriteVector(cx.Vector{\n    1, \"1\", time.Now(),\n})\n// safe way\nwriteAPI.TryWriteVector(cx.Vector{\n    1, \"1\", time.Now(),\n})\n```\n\nWhen using a non-blocking record, you can track errors through a special error channel\n\n```go\nerrorsCh := writeAPI.Errors()\ngo func() {\n    for err := range errorsCh {\n        log.Warning(fmt.Sprintf(\"clickhouse write error: %s\", err.Error()))\n    }\n}()\n```\n\nUsing the blocking writer interface\n\n```go\n// create new writer api: table name with columns\nwriterBlocking := client.WriterBlocking(cx.View{\n    Name:    \"clickhouse_database.my_table\",\n    Columns: []string{\"id\", \"uuid\", \"insert_ts\"},\n})\n// non-asynchronous writing of data directly to Clickhouse\nerr := writerBlocking.WriteRow(ctx, []*MyTable{\n    {\n        id: 1, uuid: \"1\", insertTS: time.Now(),\n    },\n    {\n        id: 2, uuid: \"2\", insertTS: time.Now(),\n    },\n    {\n        id: 3, uuid: \"3\", insertTS: time.Now(),\n    },\n}...)\n```\n\n### More\n\n#### Buffer engine:\n\nYou can implement own data-buffer interface: `File`, `Rabbitmq`, `CustomMemory`, etc.\n\n```go\ntype Buffer interface {\n    Write(vec Vector)\n    Read() []Vector\n    Len() int\n    Flush()\n}\n```\n\n#### Retries:\n\n\u003e By default, packet resending is disabled, to enable it, you need to call `(*Options).SetRetryIsEnabled(true)`.\n\n- [x] in-memory use channels (default)\n- [ ] redis\n- [ ] rabbitMQ\n- [ ] kafka\n\nYou can implement queue engine by defining the `Queueable` interface:\n\n```go\ntype Queueable interface {\n    Queue(packet *Packet)\n    Retries() \u003c-chan *Packet\n}\n\n// and set it as an engine:\nclickhousebuffer.NewOptions(\n    clickhousebuffer.WithRetry(false),\n    clickhousebuffer.WithRetryQueueEngine(CustomQueueable),\n)\n```\n\n#### Logs:\n\nYou can implement your logger by simply implementing the Logger interface and throwing it in options:\n\n```go\ntype Logger interface {\n    Log(message interface{})\n    Logf(format string, v ...interface{})\n}\n\n// example with options\nclickhousebuffer.NewOptions(\n    clickhousebuffer.WithDebugMode(true),\n    clickhousebuffer.WithLogger(SomeLogger),\n)\n```\n\n#### Tests:\n\n- `$ go test -v ./...` - run all tests without integration part\n- `$ go test -race -v ./...` - run all tests without integration part and in race detection mode\n- `$ golangci-lint run --config ./.golangci.yml` - check code quality with linters\n\n**Integration Tests:**\n\n```shell\nexport CLICKHOUSE_HOST=111.11.11.11:9000\nexport REDIS_HOST=111.11.11.11:6379\nexport REDIS_PASS=password_if_needed\n\n$ go test -v ./... -tags=integration\n\nor with race detec mode\n\n$ go test -race -v ./... -tags=integration\n```\n\n**Benchmarks**\n\n**Ubuntu 20.04/Intel Core i7-8750H**\n\n```shell\ngoos: linux\ngoarch: amd64\npkg: github.com/zikwall/clickhouse-buffer/v4/bench\ncpu: Intel(R) Core(TM) i7-8750H CPU @ 2.20GHz\n```\n\n```shell\n// memory\n\n$ go test ./bench -bench=BenchmarkInsertSimplestPreallocateVectors -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestPreallocateVectors/1000000-12                1000            142919 ns/op               0 B/op         0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/100000-12                 1000             12498 ns/op               0 B/op         0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/10000-12                  1000              1265 ns/op               0 B/op         0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/1000-12                   1000               143.1 ns/op             0 B/op         0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/100-12                    1000                 5.700 ns/op           2 B/op         0 allocs/op\n\n$ go test ./bench -bench=BenchmarkInsertSimplestPreallocateObjects -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestPreallocateObjects/1000000-12                1000            399110 ns/op           88000 B/op      3000 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/100000-12                 1000             37527 ns/op            8800 B/op       300 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/10000-12                  1000              3880 ns/op             880 B/op        30 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/1000-12                   1000               419.5 ns/op            88 B/op         3 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/100-12                    1000                58.90 ns/op           11 B/op         0 allocs/op\n\n$ go test ./bench -bench=BenchmarkInsertSimplestObjects -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestObjects/1000000-12                   1000            454794 ns/op          160002 B/op       4000 allocs/op\nBenchmarkInsertSimplestObjects/100000-12                    1000             41879 ns/op           16000 B/op        400 allocs/op\nBenchmarkInsertSimplestObjects/10000-12                     1000              4174 ns/op            1605 B/op         40 allocs/op\nBenchmarkInsertSimplestObjects/1000-12                      1000               479.5 ns/op           160 B/op          4 allocs/op\nBenchmarkInsertSimplestObjects/100-12                       1000                39.40 ns/op           16 B/op          0 allocs/op\n\n$ go test ./bench -bench=BenchmarkInsertSimplestVectors -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestVectors/1000000-12                   1000            182548 ns/op           72002 B/op       1000 allocs/op\nBenchmarkInsertSimplestVectors/100000-12                    1000             16291 ns/op            7200 B/op        100 allocs/op\nBenchmarkInsertSimplestVectors/10000-12                     1000              1638 ns/op             725 B/op         10 allocs/op\nBenchmarkInsertSimplestVectors/1000-12                      1000               208.4 ns/op            72 B/op          1 allocs/op\nBenchmarkInsertSimplestVectors/100-12                       1000                20.00 ns/op            7 B/op          0 allocs/op\n\n$ go test ./bench -bench=BenchmarkInsertSimplestEmptyVectors -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestEmptyVectors/1000000-12              1000            132887 ns/op           24002 B/op          0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/100000-12               1000             13404 ns/op            2400 B/op          0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/10000-12                1000              1299 ns/op             245 B/op          0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/1000-12                 1000               122.1 ns/op             0 B/op          0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/100-12                  1000                 6.800 ns/op           0 B/op          0 allocs/op\n\n// redis\n\n$ go test ./bench -bench=BenchmarkInsertRedisObjects -benchmem -benchtime=100x\n\nBenchmarkInsertRedisObjects/1000-12                      100          22404356 ns/op           96095 B/op       2322 allocs/op\nBenchmarkInsertRedisObjects/100-12                       100           2243544 ns/op            9673 B/op        233 allocs/op\nBenchmarkInsertRedisObjects/10-12                        100            271749 ns/op            1033 B/op         25 allocs/op\n\n$ go test ./bench -bench=BenchmarkInsertRedisVectors -benchmem -benchtime=100x\n\nBenchmarkInsertRedisVectors/1000-12                  100          22145258 ns/op           92766 B/op       2274 allocs/op\nBenchmarkInsertRedisVectors/100-12                   100           2320692 ns/op            9339 B/op        229 allocs/op\nBenchmarkInsertRedisVectors/10-12                    100            202146 ns/op             157 B/op          2 allocs/op\n```\n\n**MacBook Pro M1**\n\n```shell\ngoos: darwin\ngoarch: arm64\npkg: github.com/zikwall/clickhouse-buffer/v4/bench\n```\n\n```shell\n$ akm@MacBook-Pro-andrey clickhouse-buffer % go test ./bench -bench=BenchmarkInsertSimplestPreallocateVectors -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestPreallocateVectors/1000000-8         \t    1000\t    206279 ns/op\t       0 B/op\t       0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/100000-8          \t    1000\t     24612 ns/op\t       0 B/op\t       0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/10000-8           \t    1000\t      2047 ns/op\t       0 B/op\t       0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/1000-8            \t    1000\t       204.0 ns/op\t       0 B/op\t       0 allocs/op\nBenchmarkInsertSimplestPreallocateVectors/100-8             \t    1000\t        22.83 ns/op\t       0 B/op\t       0 allocs/op\n\n$ akm@MacBook-Pro-andrey clickhouse-buffer % go test ./bench -bench=BenchmarkInsertSimplestPreallocateObjects -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestPreallocateObjects/1000000-8         \t    1000\t    410757 ns/op\t   88000 B/op\t    3000 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/100000-8          \t    1000\t     40885 ns/op\t    8800 B/op\t     300 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/10000-8           \t    1000\t      4059 ns/op\t     880 B/op\t      30 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/1000-8            \t    1000\t       407.2 ns/op\t      88 B/op\t       3 allocs/op\nBenchmarkInsertSimplestPreallocateObjects/100-8             \t    1000\t        46.29 ns/op\t      11 B/op\t       0 allocs/op\n\n$ akm@MacBook-Pro-andrey clickhouse-buffer % go test ./bench -bench=BenchmarkInsertSimplestObjects -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestObjects/1000000-8         \t    1000\t    454083 ns/op\t  160002 B/op\t    4000 allocs/op\nBenchmarkInsertSimplestObjects/100000-8          \t    1000\t     44329 ns/op\t   16000 B/op\t     400 allocs/op\nBenchmarkInsertSimplestObjects/10000-8           \t    1000\t      4401 ns/op\t    1360 B/op\t      40 allocs/op\nBenchmarkInsertSimplestObjects/1000-8            \t    1000\t       437.8 ns/op\t     160 B/op\t       4 allocs/op\nBenchmarkInsertSimplestObjects/100-8             \t    1000\t        44.71 ns/op\t      16 B/op\t       0 allocs/op\n\n\n$ akm@MacBook-Pro-andrey clickhouse-buffer % go test ./bench -bench=BenchmarkInsertSimplestVectors -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestVectors/1000000-8         \t    1000\t    244064 ns/op\t   72002 B/op\t    1000 allocs/op\nBenchmarkInsertSimplestVectors/100000-8          \t    1000\t     24013 ns/op\t    7200 B/op\t     100 allocs/op\nBenchmarkInsertSimplestVectors/10000-8           \t    1000\t      2335 ns/op\t     725 B/op\t      10 allocs/op\nBenchmarkInsertSimplestVectors/1000-8            \t    1000\t       240.4 ns/op\t      48 B/op\t       1 allocs/op\nBenchmarkInsertSimplestVectors/100-8             \t    1000\t        22.17 ns/op\t       4 B/op\t       0 allocs/op\n\n$ akm@MacBook-Pro-andrey clickhouse-buffer % go test ./bench -bench=BenchmarkInsertSimplestEmptyVectors -benchmem -benchtime=1000x\n\nBenchmarkInsertSimplestEmptyVectors/1000000-8         \t    1000\t    215240 ns/op\t   24002 B/op\t       0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/100000-8          \t    1000\t     20736 ns/op\t    2400 B/op\t       0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/10000-8           \t    1000\t      2109 ns/op\t       0 B/op\t       0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/1000-8            \t    1000\t       198.3 ns/op\t      24 B/op\t       0 allocs/op\nBenchmarkInsertSimplestEmptyVectors/100-8             \t    1000\t        19.83 ns/op\t       2 B/op\t       0 allocs/op\n```\n\n**Conclusion:**\n\n- buffer on redis is expected to work slower than the buffer in memory, this is due to fact that it is necessary to serialize data and deserialize it back, which causes a lot of overhead, also do not forget about network overhead\n- writing through a vector causes less overhead (allocations) and works faster\n- pre-allocated vector recording works very fast with zero memory allocation, this is fact that writing to buffer and then writing it to Clickhouse creates almost no overhead\n- the same can be said about recording objects, but there is a small overhead\n- writing vectors is faster, allocates less memory, and is preferable to writing objects\n- using a buffer in-memory is preferable to a buffer in redis\n\n### TODO:\n\n- [ ] rewrite Buffer interface, simplify it\n- [ ] rewrite Options, simplify it\n- [ ] optimization redis buffer and encode/decode functions\n- [ ] buffer interfaces\n- [ ] more retry buffer interfaces\n- [ ] rewrite retry lib, simplify it\n- [ ] create binary app for streaming data to clickhouse\n  - [ ] client and server with HTTP interface\n  - [ ] client and server with gRPC interface","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzikwall%2Fclickhouse-buffer","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzikwall%2Fclickhouse-buffer","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzikwall%2Fclickhouse-buffer/lists"}