/
test_shard_by_query_utils.go
500 lines (468 loc) · 22.3 KB
/
test_shard_by_query_utils.go
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package tripperware
import (
"context"
"encoding/base64"
"fmt"
"io"
"net/http"
"net/http/httptest"
"net/url"
"sort"
"testing"
"time"
"github.com/go-kit/log"
"github.com/prometheus/common/model"
"github.com/prometheus/prometheus/promql/parser"
"github.com/stretchr/testify/require"
thanosquerysharding "github.com/thanos-io/thanos/pkg/querysharding"
"github.com/thanos-io/thanos/pkg/store/storepb"
"github.com/weaveworks/common/user"
"github.com/cortexproject/cortex/pkg/querysharding"
)
func TestQueryShardQuery(t *testing.T, instantQueryCodec Codec, shardedPrometheusCodec Codec) {
//parallel testing causes data race
type queries struct {
name string
expression string
shardingLabels []string
}
nonShardable := []queries{
{
name: "aggregation",
expression: "sum(http_requests_total)",
},
{
name: "outer aggregation with no grouping",
expression: "count(sum by (pod) (http_requests_total))",
},
{
name: "outer aggregation with without grouping",
expression: "count(sum without (pod) (http_requests_total))",
},
{
name: "binary expression with constant",
expression: `http_requests_total{code="400"} / 4`,
},
{
name: "binary expression with empty vector matching",
expression: `http_requests_total{code="400"} / on () http_requests_total`,
},
{
name: "binary aggregation with different grouping labels",
expression: `sum by (pod) (http_requests_total{code="400"}) / sum by (cluster) (http_requests_total)`,
},
{
name: "multiple binary expressions with empty vector matchers",
expression: `
(http_requests_total{code="400"} + on (cluster, pod) http_requests_total{code="500"})
/ on ()
http_requests_total`,
},
{
name: "problematic query",
expression: `sum(a by(lanel)`,
},
{
name: "aggregate by expression with label_replace, sharding label is dynamic",
expression: `sum by (dst_label) (label_replace(metric, "dst_label", "$1", "src_label", "re"))`,
},
{
name: "aggregate by expression with label_join, sharding label is dynamic",
expression: `sum by (dst_label) (label_join(metric, "dst_label", ",", "src_label"))`,
},
}
shardableByLabels := []queries{
{
name: "aggregation with grouping",
expression: "sum by (pod) (http_requests_total)",
shardingLabels: []string{"pod"},
},
{
name: "aggregation with comparison",
expression: "avg by (Roles,type) (rss_service_message_handling) > 0.5",
shardingLabels: []string{"Roles", "type"},
},
{
name: "multiple aggregations with grouping",
expression: "max by (pod) (sum by (pod, cluster) (http_requests_total))",
shardingLabels: []string{"pod"},
},
{
name: "binary expression with vector matching",
expression: `http_requests_total{code="400"} / on (pod) http_requests_total`,
shardingLabels: []string{"pod"},
},
{
name: "binary aggregation with same grouping labels",
expression: `sum by (pod) (http_requests_total{code="400"}) / sum by (pod) (http_requests_total)`,
shardingLabels: []string{"pod"},
},
{
name: "binary expression with vector matching and grouping",
expression: `sum by (cluster, pod) (http_requests_total{code="400"}) / on (pod) sum by (cluster, pod) (http_requests_total)`,
shardingLabels: []string{"pod"},
},
{
name: "multiple binary expressions with vector matchers",
expression: `
(http_requests_total{code="400"} + on (cluster, pod) http_requests_total{code="500"})
/ on (pod)
http_requests_total`,
shardingLabels: []string{"pod"},
},
{
name: "multiple binary expressions with grouping",
expression: `
sum by (container) (
(http_requests_total{code="400"} + on (cluster, pod, container) http_requests_total{code="500"})
/ on (pod, container)
http_requests_total
)`,
shardingLabels: []string{"container"},
},
{
name: "multiple binary expressions with grouping",
expression: `(http_requests_total{code="400"} + on (pod) http_requests_total{code="500"}) / on (cluster, pod) http_requests_total`,
shardingLabels: []string{"pod"},
},
{
name: "histogram quantile",
expression: "histogram_quantile(0.95, sum(rate(metric[1m])) by (le, cluster))",
shardingLabels: []string{"cluster"},
},
{
name: "aggregate by expression with label_replace, sharding label is not dynamic",
expression: `sum by (pod) (label_replace(metric, "dst_label", "$1", "src_label", "re"))`,
shardingLabels: []string{"pod"},
},
{
name: "aggregate by expression with label_join, sharding label is not dynamic",
expression: `sum by (pod) (label_join(metric, "dst_label", ",", "src_label"))`,
shardingLabels: []string{"pod"},
},
{
name: "label_join and aggregation on multiple labels. Can be sharded by the static one",
expression: `sum by (pod, dst_label) (label_join(metric, "dst_label", ",", "src_label"))`,
shardingLabels: []string{"pod"},
},
{
name: "binary expression with vector matching and label_replace",
expression: `http_requests_total{code="400"} / on (pod) label_replace(metric, "dst_label", "$1", "src_label", "re")`,
shardingLabels: []string{"pod"},
},
{
name: "nested label joins",
expression: `label_join(sum by (pod) (label_join(metric, "dst_label", ",", "src_label")), "dst_label1", ",", "dst_label")`,
shardingLabels: []string{"pod"},
},
{
name: "complex query with label_replace, binary expr and aggregations on dynamic label",
expression: `sum(sum_over_time(container_memory_working_set_bytes{container_name!="POD",container_name!="",namespace="kube-system"}[1d:5m])) by (instance, cluster) / avg(label_replace(sum(sum_over_time(kube_node_status_capacity_memory_bytes[1d:5m])) by (node, cluster), "instance", "$1", "node", "(.*)")) by (instance, cluster)`,
shardingLabels: []string{"cluster"},
},
{
name: "complex query with label_replace and nested aggregations",
expression: `avg(label_replace(label_replace(avg(count_over_time(kube_pod_container_resource_requests{resource="memory", unit="byte", container!="",container!="POD", node!="", }[1h] )*avg_over_time(kube_pod_container_resource_requests{resource="memory", unit="byte", container!="",container!="POD", node!="", }[1h] )) by (namespace,container,pod,node,cluster_id) , "container_name","$1","container","(.+)"), "pod_name","$1","pod","(.+)")) by (namespace,container_name,pod_name,node,cluster_id)`,
shardingLabels: []string{"namespace", "node", "cluster_id"},
},
{
name: "complex query with label_replace, nested aggregations and binary expressions",
expression: `sort_desc(avg(label_replace(label_replace(label_replace(count_over_time(container_memory_working_set_bytes{container!="", container!="POD", instance!="", }[1h] ), "node", "$1", "instance", "(.+)"), "container_name", "$1", "container", "(.+)"), "pod_name", "$1", "pod", "(.+)")*label_replace(label_replace(label_replace(avg_over_time(container_memory_working_set_bytes{container!="", container!="POD", instance!="", }[1h] ), "node", "$1", "instance", "(.+)"), "container_name", "$1", "container", "(.+)"), "pod_name", "$1", "pod", "(.+)")) by (namespace, container_name, pod_name, node, cluster_id))`,
shardingLabels: []string{"namespace", "cluster_id"},
},
{
name: "aggregate expression with label_replace",
expression: `sum by (pod) (label_replace(metric, "dst_label", "$1", "src_label", "re"))`,
shardingLabels: []string{"pod"},
},
}
// Shardable by labels instant queries with matrix response
shardableByLabelsMatrix := []queries{
{
name: "subquery",
expression: "sum(http_requests_total) by (pod, cluster) [1h:1m]",
shardingLabels: []string{"cluster", "pod"},
},
{
name: "subquery with function",
expression: "increase(sum(http_requests_total) by (pod, cluster) [1h:1m])",
shardingLabels: []string{"cluster", "pod"},
},
{
name: "ignore vector matching with 2 aggregations",
expression: `sum(rate(node_cpu_seconds_total[3h])) by (cluster_id, mode) / ignoring(mode) group_left sum(rate(node_cpu_seconds_total[3h])) by (cluster_id)`,
shardingLabels: []string{"cluster_id"},
},
}
shardableWithoutLabels := []queries{
{
name: "aggregation without grouping",
expression: "sum without (pod) (http_requests_total)",
shardingLabels: []string{"pod"},
},
{
name: "multiple aggregations with without grouping",
expression: "max without (pod) (sum without (pod, cluster) (http_requests_total))",
shardingLabels: []string{"pod", "cluster"},
},
{
name: "binary expression with without vector matching and grouping",
expression: `sum without (cluster, pod) (http_requests_total{code="400"}) / ignoring (pod) sum without (cluster, pod) (http_requests_total)`,
shardingLabels: []string{"pod", "cluster", model.MetricNameLabel},
},
{
name: "binary expression with outer without grouping",
expression: `sum(http_requests_total{code="400"} * http_requests_total) without (pod)`,
shardingLabels: []string{model.MetricNameLabel, "pod"},
},
{
name: "binary expression with vector matching and outer without grouping",
expression: `sum(http_requests_total{code="400"} * ignoring(cluster) http_requests_total) without ()`,
shardingLabels: []string{"__name__", "cluster"},
},
{
name: "multiple binary expressions with without grouping",
expression: `(http_requests_total{code="400"} + ignoring (pod) http_requests_total{code="500"}) / ignoring (cluster, pod) http_requests_total`,
shardingLabels: []string{"cluster", "pod", model.MetricNameLabel},
},
{
name: "multiple binary expressions with without vector matchers",
expression: `
(http_requests_total{code="400"} + ignoring (cluster, pod) http_requests_total{code="500"})
/ ignoring (pod)
http_requests_total`,
shardingLabels: []string{"cluster", "pod", model.MetricNameLabel},
},
{
name: "aggregate without expression with label_replace, sharding label is not dynamic",
expression: `sum without (dst_label) (label_replace(metric, "dst_label", "$1", "src_label", "re"))`,
shardingLabels: []string{"dst_label"},
},
{
name: "aggregate without expression with label_join, sharding label is not dynamic",
expression: `sum without (dst_label) (label_join(metric, "dst_label", ",", "src_label"))`,
shardingLabels: []string{"dst_label"},
},
{
name: "aggregate without expression with label_replace",
expression: `sum without (pod) (label_replace(metric, "dst_label", "$1", "src_label", "re"))`,
shardingLabels: []string{"pod", "dst_label"},
},
{
name: "binary expression",
expression: `http_requests_total{code="400"} / http_requests_total`,
shardingLabels: []string{model.MetricNameLabel},
},
{
name: "binary expression among vector and scalar",
expression: `aaaa - bbb > 1000`,
shardingLabels: []string{model.MetricNameLabel},
},
{
name: "binary expression with set operation",
expression: `aaaa and bbb`,
shardingLabels: []string{model.MetricNameLabel},
},
{
name: "multiple binary expressions",
expression: `(http_requests_total{code="400"} + http_requests_total{code="500"}) / http_requests_total`,
shardingLabels: []string{model.MetricNameLabel},
},
}
type testCase struct {
name string
path string
isShardable bool
shardSize int
codec Codec
responses []string
response string
shardingLabels []string
}
tests := []testCase{
{
name: "should shard range query when query is shardable",
path: `/api/v1/query_range?end=1&start=0&step=120&query=sum(metric) by (pod,cluster_name)`,
isShardable: true,
codec: shardedPrometheusCodec,
shardingLabels: []string{"pod", "cluster_name"},
shardSize: 2,
responses: []string{
`{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__name__":"metric","__job__":"a"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":6,"totalQueryableSamplesPerStep":[[1,1],[2,2],[3,3]]}}}}`,
`{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__name__":"metric","__job__":"b"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":6,"totalQueryableSamplesPerStep":[[1,1],[2,2],[3,3]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__job__":"a","__name__":"metric"},"values":[[1,"1"],[2,"2"],[3,"3"]]},{"metric":{"__job__":"b","__name__":"metric"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":12,"totalQueryableSamplesPerStep":[[1,2],[2,4],[3,6]]}}}}`,
},
{
name: "should shard instant query when query is shardable",
path: `/api/v1/query?time=120&query=sum(metric) by (pod,cluster_name)`,
codec: instantQueryCodec,
shardSize: 2,
shardingLabels: []string{"pod", "cluster_name"},
isShardable: true,
responses: []string{
`{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
`{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"bar"},"value":[2,"2"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"bar"},"value":[2,"2"]},{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":20,"totalQueryableSamplesPerStep":[[1,20]]}}}}`,
},
{
name: "should not shard if shard size is 1",
path: `/api/v1/query?time=120&query=sum(metric) by (pod,cluster_name)`,
codec: instantQueryCodec,
shardSize: 1,
isShardable: false,
responses: []string{
`{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
},
}
for _, query := range nonShardable {
tests = append(tests, testCase{
name: fmt.Sprintf("non shardable query: %s", query.name),
path: fmt.Sprintf(`/api/v1/query?time=120&query=%s`, url.QueryEscape(query.expression)),
codec: instantQueryCodec,
shardSize: 2,
isShardable: false,
responses: []string{
`{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
})
tests = append(tests, testCase{
name: fmt.Sprintf("non shardable query_range: %s", query.name),
path: fmt.Sprintf(`/api/v1/query_range?start=1&end=2&step=1&query=%s`, url.QueryEscape(query.expression)),
codec: shardedPrometheusCodec,
shardSize: 2,
isShardable: false,
responses: []string{
`{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__job__":"a","__name__":"metric"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":6,"totalQueryableSamplesPerStep":[[1,1],[2,2],[3,3]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__job__":"a","__name__":"metric"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":6,"totalQueryableSamplesPerStep":[[1,1],[2,2],[3,3]]}}}}`,
})
}
for _, query := range append(shardableWithoutLabels, shardableByLabels...) {
tests = append(tests, testCase{
name: fmt.Sprintf("shardable query: %s", query.name),
path: fmt.Sprintf(`/api/v1/query?time=120&query=%s`, url.QueryEscape(query.expression)),
codec: instantQueryCodec,
isShardable: true,
shardSize: 2,
shardingLabels: query.shardingLabels,
responses: []string{
`{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
`{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"bar"},"value":[2,"2"]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"vector","result":[{"metric":{"__name__":"up","job":"bar"},"value":[2,"2"]},{"metric":{"__name__":"up","job":"foo"},"value":[1,"1"]}],"stats":{"samples":{"totalQueryableSamples":20,"totalQueryableSamplesPerStep":[[1,20]]}}}}`,
})
tests = append(tests, testCase{
name: fmt.Sprintf("shardable query_range: %s", query.name),
path: fmt.Sprintf(`/api/v1/query_range?start=1&end=2&step=1&query=%s`, url.QueryEscape(query.expression)),
codec: shardedPrometheusCodec,
isShardable: true,
shardSize: 2,
shardingLabels: query.shardingLabels,
responses: []string{
`{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__name__":"metric","__job__":"a"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":6,"totalQueryableSamplesPerStep":[[1,1],[2,2],[3,3]]}}}}`,
`{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__name__":"metric","__job__":"b"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":6,"totalQueryableSamplesPerStep":[[1,1],[2,2],[3,3]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__job__":"a","__name__":"metric"},"values":[[1,"1"],[2,"2"],[3,"3"]]},{"metric":{"__job__":"b","__name__":"metric"},"values":[[1,"1"],[2,"2"],[3,"3"]]}],"stats":{"samples":{"totalQueryableSamples":12,"totalQueryableSamplesPerStep":[[1,2],[2,4],[3,6]]}}}}`,
})
}
for _, query := range shardableByLabelsMatrix {
tests = append(tests, testCase{
name: fmt.Sprintf("shardable query: %s", query.name),
path: fmt.Sprintf(`/api/v1/query?time=120&query=%s`, url.QueryEscape(query.expression)),
codec: instantQueryCodec,
isShardable: true,
shardSize: 2,
shardingLabels: query.shardingLabels,
responses: []string{
`{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__name__":"up","job":"foo"},"values":[[1,"1"]]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
`{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__name__":"up","job":"bar"},"values":[[2,"2"]]}],"stats":{"samples":{"totalQueryableSamples":10,"totalQueryableSamplesPerStep":[[1,10]]}}}}`,
},
response: `{"status":"success","data":{"resultType":"matrix","result":[{"metric":{"__name__":"up","job":"bar"},"values":[[2,"2"]]},{"metric":{"__name__":"up","job":"foo"},"values":[[1,"1"]]}],"stats":{"samples":{"totalQueryableSamples":20,"totalQueryableSamplesPerStep":[[1,20]]}}}}`,
})
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
//parallel testing causes data race
sort.Strings(tt.shardingLabels)
s := httptest.NewServer(
http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
q := r.FormValue("query")
expr, _ := parser.ParseExpr(q)
shardIndex := int64(0)
parser.Inspect(expr, func(n parser.Node, _ []parser.Node) error {
if selector, ok := n.(*parser.VectorSelector); ok {
for _, matcher := range selector.LabelMatchers {
if matcher.Name == querysharding.CortexShardByLabel {
decoded, _ := base64.StdEncoding.DecodeString(matcher.Value)
shardInfo := storepb.ShardInfo{}
err := shardInfo.Unmarshal(decoded)
require.NoError(t, err)
sort.Strings(shardInfo.Labels)
require.Equal(t, tt.shardingLabels, shardInfo.Labels)
require.Equal(t, tt.isShardable, shardInfo.TotalShards > 0)
shardIndex = shardInfo.ShardIndex
}
}
}
return nil
})
_, _ = w.Write([]byte(tt.responses[shardIndex]))
}),
)
defer s.Close()
u, err := url.Parse(s.URL)
require.NoError(t, err)
downstream := singleHostRoundTripper{
host: u.Host,
next: http.DefaultTransport,
}
qa := thanosquerysharding.NewQueryAnalyzer()
roundtripper := NewRoundTripper(downstream, tt.codec, nil, ShardByMiddleware(log.NewNopLogger(), mockLimits{shardSize: tt.shardSize}, tt.codec, qa))
ctx := user.InjectOrgID(context.Background(), "1")
req, err := http.NewRequest("GET", tt.path, http.NoBody)
req = req.WithContext(ctx)
require.NoError(t, err)
resp, err := roundtripper.RoundTrip(req)
require.NoError(t, err)
require.NotNil(t, resp)
contents, err := io.ReadAll(resp.Body)
require.NoError(t, err)
require.Equal(t, tt.response, string(contents))
})
}
}
type mockLimits struct {
maxQueryLookback time.Duration
maxQueryLength time.Duration
maxCacheFreshness time.Duration
shardSize int
}
func (m mockLimits) MaxQueryLookback(string) time.Duration {
return m.maxQueryLookback
}
func (m mockLimits) MaxQueryLength(string) time.Duration {
return m.maxQueryLength
}
func (mockLimits) MaxQueryParallelism(string) int {
return 14 // Flag default.
}
func (m mockLimits) MaxCacheFreshness(string) time.Duration {
return m.maxCacheFreshness
}
func (m mockLimits) QueryVerticalShardSize(userID string) int {
return m.shardSize
}
type singleHostRoundTripper struct {
host string
next http.RoundTripper
}
func (s singleHostRoundTripper) RoundTrip(r *http.Request) (*http.Response, error) {
r.URL.Scheme = "http"
r.URL.Host = s.host
return s.next.RoundTrip(r)
}