[Rollup] Only allow aggregating on multiples of configured interval (#32052)

We need to limit the search request aggregations to whole multiples
of the configured interval for both histogram and date_histogram.
Otherwise, agg buckets won't overlap with the rolled up buckets
and the results will be incorrect.

For histogram, the validation is very simple: request must be >= the config,
and modulo evenly.

Dates are more tricky.
- If both request and config are fixed dates, we can convert to millis
and treat them just like the histo
- If both are calendar, we make sure the request is >= the config with
a static lookup map that ranks the calendar values relatively.  All
calendar units are "singles", so they are evenly divisible already
- We disallow any other combination (one fixed, one calendar, etc)
This commit is contained in:
Zachary Tong 2018-08-29 17:10:00 -04:00 committed by GitHub
parent 13880bd8c1
commit d93b2a2e9a
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8 changed files with 380 additions and 84 deletions

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@ -685,9 +685,8 @@ setups['sensor_prefab_data'] = '''
page_size: 1000
groups:
date_histogram:
delay: "7d"
field: "timestamp"
interval: "1h"
interval: "7d"
time_zone: "UTC"
terms:
fields:

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@ -43,6 +43,8 @@ started with the <<rollup-start-job,Start Job API>>.
`metrics`::
(object) Defines the metrics that should be collected for each grouping tuple. See <<rollup-job-config,rollup job config>>.
For more details about the job configuration, see <<rollup-job-config>>.
==== Authorization
You must have `manage` or `manage_rollup` cluster privileges to use this API.

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@ -23,7 +23,7 @@ PUT _xpack/rollup/job/sensor
"groups" : {
"date_histogram": {
"field": "timestamp",
"interval": "1h",
"interval": "60m",
"delay": "7d"
},
"terms": {
@ -99,7 +99,7 @@ fields will then be available later for aggregating into buckets. For example,
"groups" : {
"date_histogram": {
"field": "timestamp",
"interval": "1h",
"interval": "60m",
"delay": "7d"
},
"terms": {
@ -133,9 +133,9 @@ The `date_histogram` group has several parameters:
The date field that is to be rolled up.
`interval` (required)::
The interval of time buckets to be generated when rolling up. E.g. `"1h"` will produce hourly rollups. This follows standard time formatting
syntax as used elsewhere in Elasticsearch. The `interval` defines the _minimum_ interval that can be aggregated only. If hourly (`"1h"`)
intervals are configured, <<rollup-search,Rollup Search>> can execute aggregations with 1hr or greater (weekly, monthly, etc) intervals.
The interval of time buckets to be generated when rolling up. E.g. `"60m"` will produce 60 minute (hourly) rollups. This follows standard time formatting
syntax as used elsewhere in Elasticsearch. The `interval` defines the _minimum_ interval that can be aggregated only. If hourly (`"60m"`)
intervals are configured, <<rollup-search,Rollup Search>> can execute aggregations with 60m or greater (weekly, monthly, etc) intervals.
So define the interval as the smallest unit that you wish to later query.
Note: smaller, more granular intervals take up proportionally more space.
@ -154,6 +154,46 @@ The `date_histogram` group has several parameters:
to be stored with a specific timezone. By default, rollup documents are stored in `UTC`, but this can be changed with the `time_zone`
parameter.
.Calendar vs Fixed time intervals
**********************************
Elasticsearch understands both "calendar" and "fixed" time intervals. Fixed time intervals are fairly easy to understand;
`"60s"` means sixty seconds. But what does `"1M` mean? One month of time depends on which month we are talking about,
some months are longer or shorter than others. This is an example of "calendar" time, and the duration of that unit
depends on context. Calendar units are also affected by leap-seconds, leap-years, etc.
This is important because the buckets generated by Rollup will be in either calendar or fixed intervals, and will limit
how you can query them later (see <<rollup-search-limitations-intervals, Requests must be multiples of the config>>.
We recommend sticking with "fixed" time intervals, since they are easier to understand and are more flexible at query
time. It will introduce some drift in your data during leap-events, and you will have to think about months in a fixed
quantity (30 days) instead of the actual calendar length... but it is often easier than dealing with calendar units
at query time.
Multiples of units are always "fixed" (e.g. `"2h"` is always the fixed quantity `7200` seconds. Single units can be
fixed or calendar depending on the unit:
[options="header"]
|=======
|Unit |Calendar |Fixed
|millisecond |NA |`1ms`, `10ms`, etc
|second |NA |`1s`, `10s`, etc
|minute |`1m` |`2m`, `10m`, etc
|hour |`1h` |`2h`, `10h`, etc
|day |`1d` |`2d`, `10d`, etc
|week |`1w` |NA
|month |`1M` |NA
|quarter |`1q` |NA
|year |`1y` |NA
|=======
For some units where there are both fixed and calendar, you may need to express the quantity in terms of the next
smaller unit. For example, if you want a fixed day (not a calendar day), you should specify `24h` instead of `1d`.
Similarly, if you want fixed hours, specify `60m` instead of `1h`. This is because the single quantity entails
calendar time, and limits you to querying by calendar time in the future.
**********************************
===== Terms
The `terms` group can be used on `keyword` or numeric fields, to allow bucketing via the `terms` aggregation at a later point. The `terms`

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@ -37,8 +37,7 @@ PUT _xpack/rollup/job/sensor
"groups" : {
"date_histogram": {
"field": "timestamp",
"interval": "1h",
"delay": "7d"
"interval": "60m"
},
"terms": {
"fields": ["node"]
@ -66,7 +65,7 @@ The `cron` parameter controls when and how often the job activates. When a roll
from where it left off after the last activation. So if you configure the cron to run every 30 seconds, the job will process the last 30
seconds worth of data that was indexed into the `sensor-*` indices.
If instead the cron was configured to run once a day at midnight, the job would process the last 24hours worth of data. The choice is largely
If instead the cron was configured to run once a day at midnight, the job would process the last 24 hours worth of data. The choice is largely
preference, based on how "realtime" you want the rollups, and if you wish to process continuously or move it to off-peak hours.
Next, we define a set of `groups` and `metrics`. The metrics are fairly straightforward: we want to save the min/max/sum of the `temperature`
@ -79,7 +78,7 @@ It also allows us to run terms aggregations on the `node` field.
.Date histogram interval vs cron schedule
**********************************
You'll note that the job's cron is configured to run every 30 seconds, but the date_histogram is configured to
rollup at hourly intervals. How do these relate?
rollup at 60 minute intervals. How do these relate?
The date_histogram controls the granularity of the saved data. Data will be rolled up into hourly intervals, and you will be unable
to query with finer granularity. The cron simply controls when the process looks for new data to rollup. Every 30 seconds it will see
@ -223,70 +222,71 @@ Which returns a corresponding response:
[source,js]
----
{
"took" : 93,
"timed_out" : false,
"terminated_early" : false,
"_shards" : ... ,
"hits" : {
"total" : 0,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"timeline" : {
"meta" : { },
"buckets" : [
{
"key_as_string" : "2018-01-18T00:00:00.000Z",
"key" : 1516233600000,
"doc_count" : 6,
"nodes" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "a",
"doc_count" : 2,
"max_temperature" : {
"value" : 202.0
},
"avg_voltage" : {
"value" : 5.1499998569488525
}
},
{
"key" : "b",
"doc_count" : 2,
"max_temperature" : {
"value" : 201.0
},
"avg_voltage" : {
"value" : 5.700000047683716
}
},
{
"key" : "c",
"doc_count" : 2,
"max_temperature" : {
"value" : 202.0
},
"avg_voltage" : {
"value" : 4.099999904632568
}
}
]
}
}
]
}
}
"took" : 93,
"timed_out" : false,
"terminated_early" : false,
"_shards" : ... ,
"hits" : {
"total" : 0,
"max_score" : 0.0,
"hits" : [ ]
},
"aggregations" : {
"timeline" : {
"meta" : { },
"buckets" : [
{
"key_as_string" : "2018-01-18T00:00:00.000Z",
"key" : 1516233600000,
"doc_count" : 6,
"nodes" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "a",
"doc_count" : 2,
"max_temperature" : {
"value" : 202.0
},
"avg_voltage" : {
"value" : 5.1499998569488525
}
},
{
"key" : "b",
"doc_count" : 2,
"max_temperature" : {
"value" : 201.0
},
"avg_voltage" : {
"value" : 5.700000047683716
}
},
{
"key" : "c",
"doc_count" : 2,
"max_temperature" : {
"value" : 202.0
},
"avg_voltage" : {
"value" : 4.099999904632568
}
}
]
}
}
]
}
}
}
----
// TESTRESPONSE[s/"took" : 93/"took" : $body.$_path/]
// TESTRESPONSE[s/"_shards" : \.\.\. /"_shards" : $body.$_path/]
In addition to being more complicated (date histogram and a terms aggregation, plus an additional average metric), you'll notice
the date_histogram uses a `7d` interval instead of `1h`.
the date_histogram uses a `7d` interval instead of `60m`.
[float]
=== Conclusion

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@ -80,9 +80,25 @@ The response will tell you that the field and aggregation were not possible, bec
[float]
=== Interval Granularity
Rollups are stored at a certain granularity, as defined by the `date_histogram` group in the configuration. If data is rolled up at hourly
intervals, the <<rollup-search>> API can aggregate on any time interval hourly or greater. Intervals that are less than an hour will throw
an exception, since the data simply doesn't exist for finer granularities.
Rollups are stored at a certain granularity, as defined by the `date_histogram` group in the configuration. This means you
can only search/aggregate the rollup data with an interval that is greater-than or equal to the configured rollup interval.
For example, if data is rolled up at hourly intervals, the <<rollup-search>> API can aggregate on any time interval
hourly or greater. Intervals that are less than an hour will throw an exception, since the data simply doesn't
exist for finer granularities.
[[rollup-search-limitations-intervals]]
.Requests must be multiples of the config
**********************************
Perhaps not immediately apparent, but the interval specified in an aggregation request must be a whole
multiple of the configured interval. If the job was configured to rollup on `3d` intervals, you can only
query and aggregate on multiples of three (`3d`, `6d`, `9d`, etc).
A non-multiple wouldn't work, since the rolled up data wouldn't cleanly "overlap" with the buckets generated
by the aggregation, leading to incorrect results.
For that reason, an error is thrown if a whole multiple of the configured interval isn't found.
**********************************
Because the RollupSearch endpoint can "upsample" intervals, there is no need to configure jobs with multiple intervals (hourly, daily, etc).
It's recommended to just configure a single job with the smallest granularity that is needed, and allow the search endpoint to upsample

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@ -8,6 +8,7 @@ package org.elasticsearch.xpack.rollup;
import org.elasticsearch.common.unit.TimeValue;
import org.elasticsearch.search.aggregations.AggregationBuilder;
import org.elasticsearch.search.aggregations.bucket.histogram.DateHistogramAggregationBuilder;
import org.elasticsearch.search.aggregations.bucket.histogram.DateHistogramInterval;
import org.elasticsearch.search.aggregations.bucket.histogram.HistogramAggregationBuilder;
import org.elasticsearch.search.aggregations.bucket.terms.TermsAggregationBuilder;
import org.elasticsearch.search.aggregations.support.ValuesSourceAggregationBuilder;
@ -17,7 +18,9 @@ import org.elasticsearch.xpack.core.rollup.job.DateHistogramGroupConfig;
import org.joda.time.DateTimeZone;
import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
@ -32,6 +35,29 @@ public class RollupJobIdentifierUtils {
private static final Comparator<RollupJobCaps> COMPARATOR = RollupJobIdentifierUtils.getComparator();
public static final Map<String, Integer> CALENDAR_ORDERING;
static {
Map<String, Integer> dateFieldUnits = new HashMap<>(16);
dateFieldUnits.put("year", 8);
dateFieldUnits.put("1y", 8);
dateFieldUnits.put("quarter", 7);
dateFieldUnits.put("1q", 7);
dateFieldUnits.put("month", 6);
dateFieldUnits.put("1M", 6);
dateFieldUnits.put("week", 5);
dateFieldUnits.put("1w", 5);
dateFieldUnits.put("day", 4);
dateFieldUnits.put("1d", 4);
dateFieldUnits.put("hour", 3);
dateFieldUnits.put("1h", 3);
dateFieldUnits.put("minute", 2);
dateFieldUnits.put("1m", 2);
dateFieldUnits.put("second", 1);
dateFieldUnits.put("1s", 1);
CALENDAR_ORDERING = Collections.unmodifiableMap(dateFieldUnits);
}
/**
* Given the aggregation tree and a list of available job capabilities, this method will return a set
* of the "best" jobs that should be searched.
@ -93,8 +119,9 @@ public class RollupJobIdentifierUtils {
if (fieldCaps != null) {
for (Map<String, Object> agg : fieldCaps.getAggs()) {
if (agg.get(RollupField.AGG).equals(DateHistogramAggregationBuilder.NAME)) {
TimeValue interval = TimeValue.parseTimeValue((String)agg.get(RollupField.INTERVAL), "date_histogram.interval");
String thisTimezone = (String) agg.get(DateHistogramGroupConfig.TIME_ZONE);
DateHistogramInterval interval = new DateHistogramInterval((String)agg.get(RollupField.INTERVAL));
String thisTimezone = (String)agg.get(DateHistogramGroupConfig.TIME_ZONE);
String sourceTimeZone = source.timeZone() == null ? DateTimeZone.UTC.toString() : source.timeZone().toString();
// Ensure we are working on the same timezone
@ -102,17 +129,20 @@ public class RollupJobIdentifierUtils {
continue;
}
if (source.dateHistogramInterval() != null) {
TimeValue sourceInterval = TimeValue.parseTimeValue(source.dateHistogramInterval().toString(),
"source.date_histogram.interval");
//TODO should be divisor of interval
if (interval.compareTo(sourceInterval) <= 0) {
// Check if both are calendar and validate if they are.
// If not, check if both are fixed and validate
if (validateCalendarInterval(source.dateHistogramInterval(), interval)) {
localCaps.add(cap);
} else if (validateFixedInterval(source.dateHistogramInterval(), interval)) {
localCaps.add(cap);
}
} else {
if (interval.getMillis() <= source.interval()) {
// check if config is fixed and validate if it is
if (validateFixedInterval(source.interval(), interval)) {
localCaps.add(cap);
}
}
// not a candidate if we get here
break;
}
}
@ -133,6 +163,55 @@ public class RollupJobIdentifierUtils {
}
}
private static boolean isCalendarInterval(DateHistogramInterval interval) {
return DateHistogramAggregationBuilder.DATE_FIELD_UNITS.containsKey(interval.toString());
}
static boolean validateCalendarInterval(DateHistogramInterval requestInterval,
DateHistogramInterval configInterval) {
// Both must be calendar intervals
if (isCalendarInterval(requestInterval) == false || isCalendarInterval(configInterval) == false) {
return false;
}
// The request must be gte the config. The CALENDAR_ORDERING map values are integers representing
// relative orders between the calendar units
int requestOrder = CALENDAR_ORDERING.getOrDefault(requestInterval.toString(), Integer.MAX_VALUE);
int configOrder = CALENDAR_ORDERING.getOrDefault(configInterval.toString(), Integer.MAX_VALUE);
// All calendar units are multiples naturally, so we just care about gte
return requestOrder >= configOrder;
}
static boolean validateFixedInterval(DateHistogramInterval requestInterval,
DateHistogramInterval configInterval) {
// Neither can be calendar intervals
if (isCalendarInterval(requestInterval) || isCalendarInterval(configInterval)) {
return false;
}
// Both are fixed, good to conver to millis now
long configIntervalMillis = TimeValue.parseTimeValue(configInterval.toString(),
"date_histo.config.interval").getMillis();
long requestIntervalMillis = TimeValue.parseTimeValue(requestInterval.toString(),
"date_histo.request.interval").getMillis();
// Must be a multiple and gte the config
return requestIntervalMillis >= configIntervalMillis && requestIntervalMillis % configIntervalMillis == 0;
}
static boolean validateFixedInterval(long requestInterval, DateHistogramInterval configInterval) {
// config must not be a calendar interval
if (isCalendarInterval(configInterval)) {
return false;
}
long configIntervalMillis = TimeValue.parseTimeValue(configInterval.toString(),
"date_histo.config.interval").getMillis();
// Must be a multiple and gte the config
return requestInterval >= configIntervalMillis && requestInterval % configIntervalMillis == 0;
}
/**
* Find the set of histo's with the largest interval
*/
@ -144,8 +223,8 @@ public class RollupJobIdentifierUtils {
for (Map<String, Object> agg : fieldCaps.getAggs()) {
if (agg.get(RollupField.AGG).equals(HistogramAggregationBuilder.NAME)) {
Long interval = (long)agg.get(RollupField.INTERVAL);
// TODO should be divisor of interval
if (interval <= source.interval()) {
// query interval must be gte the configured interval, and a whole multiple
if (interval <= source.interval() && source.interval() % interval == 0) {
localCaps.add(cap);
}
break;
@ -155,8 +234,8 @@ public class RollupJobIdentifierUtils {
}
if (localCaps.isEmpty()) {
throw new IllegalArgumentException("There is not a rollup job that has a [" + source.getWriteableName() + "] agg on field [" +
source.field() + "] which also satisfies all requirements of query.");
throw new IllegalArgumentException("There is not a rollup job that has a [" + source.getWriteableName()
+ "] agg on field [" + source.field() + "] which also satisfies all requirements of query.");
}
// We are a leaf, save our best caps

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@ -61,6 +61,32 @@ public class RollupJobIdentifierUtilTests extends ESTestCase {
assertThat(bestCaps.size(), equalTo(1));
}
public void testBiggerButCompatibleFixedInterval() {
final GroupConfig group = new GroupConfig(new DateHistogramGroupConfig("foo", new DateHistogramInterval("100s")));
final RollupJobConfig job = new RollupJobConfig("foo", "index", "rollup", "*/5 * * * * ?", 10, group, emptyList(), null);
RollupJobCaps cap = new RollupJobCaps(job);
Set<RollupJobCaps> caps = singletonSet(cap);
DateHistogramAggregationBuilder builder = new DateHistogramAggregationBuilder("foo").field("foo")
.dateHistogramInterval(new DateHistogramInterval("1000s"));
Set<RollupJobCaps> bestCaps = RollupJobIdentifierUtils.findBestJobs(builder, caps);
assertThat(bestCaps.size(), equalTo(1));
}
public void testBiggerButCompatibleFixedMillisInterval() {
final GroupConfig group = new GroupConfig(new DateHistogramGroupConfig("foo", new DateHistogramInterval("100ms")));
final RollupJobConfig job = new RollupJobConfig("foo", "index", "rollup", "*/5 * * * * ?", 10, group, emptyList(), null);
RollupJobCaps cap = new RollupJobCaps(job);
Set<RollupJobCaps> caps = singletonSet(cap);
DateHistogramAggregationBuilder builder = new DateHistogramAggregationBuilder("foo").field("foo")
.interval(1000);
Set<RollupJobCaps> bestCaps = RollupJobIdentifierUtils.findBestJobs(builder, caps);
assertThat(bestCaps.size(), equalTo(1));
}
public void testIncompatibleInterval() {
final GroupConfig group = new GroupConfig(new DateHistogramGroupConfig("foo", new DateHistogramInterval("1d")));
final RollupJobConfig job = new RollupJobConfig("foo", "index", "rollup", "*/5 * * * * ?", 10, group, emptyList(), null);
@ -75,6 +101,20 @@ public class RollupJobIdentifierUtilTests extends ESTestCase {
"[foo] which also satisfies all requirements of query."));
}
public void testIncompatibleFixedCalendarInterval() {
final GroupConfig group = new GroupConfig(new DateHistogramGroupConfig("foo", new DateHistogramInterval("5d")));
final RollupJobConfig job = new RollupJobConfig("foo", "index", "rollup", "*/5 * * * * ?", 10, group, emptyList(), null);
RollupJobCaps cap = new RollupJobCaps(job);
Set<RollupJobCaps> caps = singletonSet(cap);
DateHistogramAggregationBuilder builder = new DateHistogramAggregationBuilder("foo").field("foo")
.dateHistogramInterval(new DateHistogramInterval("day"));
RuntimeException e = expectThrows(RuntimeException.class, () -> RollupJobIdentifierUtils.findBestJobs(builder, caps));
assertThat(e.getMessage(), equalTo("There is not a rollup job that has a [date_histogram] agg on field " +
"[foo] which also satisfies all requirements of query."));
}
public void testBadTimeZone() {
final GroupConfig group = new GroupConfig(new DateHistogramGroupConfig("foo", new DateHistogramInterval("1h"), null, "EST"));
final RollupJobConfig job = new RollupJobConfig("foo", "index", "rollup", "*/5 * * * * ?", 10, group, emptyList(), null);
@ -385,6 +425,27 @@ public class RollupJobIdentifierUtilTests extends ESTestCase {
"[bar] which also satisfies all requirements of query."));
}
public void testHistoIntervalNotMultiple() {
HistogramAggregationBuilder histo = new HistogramAggregationBuilder("test_histo");
histo.interval(10) // <--- interval is not a multiple of 3
.field("bar")
.subAggregation(new MaxAggregationBuilder("the_max").field("max_field"))
.subAggregation(new AvgAggregationBuilder("the_avg").field("avg_field"));
final GroupConfig group = new GroupConfig(new DateHistogramGroupConfig("foo",
new DateHistogramInterval("1d"), null, "UTC"),
new HistogramGroupConfig(3L, "bar"),
null);
final RollupJobConfig job = new RollupJobConfig("foo", "index", "rollup", "*/5 * * * * ?", 10, group, emptyList(), null);
RollupJobCaps cap = new RollupJobCaps(job);
Set<RollupJobCaps> caps = singletonSet(cap);
Exception e = expectThrows(RuntimeException.class,
() -> RollupJobIdentifierUtils.findBestJobs(histo, caps));
assertThat(e.getMessage(), equalTo("There is not a rollup job that has a [histogram] agg on field " +
"[bar] which also satisfies all requirements of query."));
}
public void testMissingMetric() {
int i = ESTestCase.randomIntBetween(0, 3);
@ -417,6 +478,105 @@ public class RollupJobIdentifierUtilTests extends ESTestCase {
}
public void testValidateFixedInterval() {
boolean valid = RollupJobIdentifierUtils.validateFixedInterval(100, new DateHistogramInterval("100ms"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(200, new DateHistogramInterval("100ms"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(1000, new DateHistogramInterval("200ms"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(5*60*1000, new DateHistogramInterval("5m"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(10*5*60*1000, new DateHistogramInterval("5m"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(100, new DateHistogramInterval("500ms"));
assertFalse(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(100, new DateHistogramInterval("5m"));
assertFalse(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(100, new DateHistogramInterval("minute"));
assertFalse(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(100, new DateHistogramInterval("second"));
assertFalse(valid);
// -----------
// Same tests, with both being DateHistoIntervals
// -----------
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("100ms"),
new DateHistogramInterval("100ms"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("200ms"),
new DateHistogramInterval("100ms"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("1000ms"),
new DateHistogramInterval("200ms"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("5m"),
new DateHistogramInterval("5m"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("20m"),
new DateHistogramInterval("5m"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("100ms"),
new DateHistogramInterval("500ms"));
assertFalse(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("100ms"),
new DateHistogramInterval("5m"));
assertFalse(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("100ms"),
new DateHistogramInterval("minute"));
assertFalse(valid);
valid = RollupJobIdentifierUtils.validateFixedInterval(new DateHistogramInterval("100ms"),
new DateHistogramInterval("second"));
assertFalse(valid);
}
public void testValidateCalendarInterval() {
boolean valid = RollupJobIdentifierUtils.validateCalendarInterval(new DateHistogramInterval("second"),
new DateHistogramInterval("second"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateCalendarInterval(new DateHistogramInterval("minute"),
new DateHistogramInterval("second"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateCalendarInterval(new DateHistogramInterval("month"),
new DateHistogramInterval("day"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateCalendarInterval(new DateHistogramInterval("1d"),
new DateHistogramInterval("1s"));
assertTrue(valid);
valid = RollupJobIdentifierUtils.validateCalendarInterval(new DateHistogramInterval("second"),
new DateHistogramInterval("minute"));
assertFalse(valid);
valid = RollupJobIdentifierUtils.validateCalendarInterval(new DateHistogramInterval("second"),
new DateHistogramInterval("1m"));
assertFalse(valid);
// Fails because both are actually fixed
valid = RollupJobIdentifierUtils.validateCalendarInterval(new DateHistogramInterval("100ms"),
new DateHistogramInterval("100ms"));
assertFalse(valid);
}
private Set<RollupJobCaps> singletonSet(RollupJobCaps cap) {
Set<RollupJobCaps> caps = new HashSet<>();
caps.add(cap);

View File

@ -173,7 +173,7 @@ public class RollupIT extends ESRestTestCase {
" \"date_histo\": {\n" +
" \"date_histogram\": {\n" +
" \"field\": \"timestamp\",\n" +
" \"interval\": \"1h\",\n" +
" \"interval\": \"60m\",\n" +
" \"format\": \"date_time\"\n" +
" },\n" +
" \"aggs\": {\n" +