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The following commit(s) were added to refs/heads/master by this push:
     new 91cd573  fixes web console introduction and addresses linking issues 
(#11609)
91cd573 is described below

commit 91cd5734727f2b0fc8aab999c711f3d5babaf82e
Author: Charles Smith <[email protected]>
AuthorDate: Wed Aug 18 08:37:05 2021 -0700

    fixes web console introduction and addresses linking issues (#11609)
    
    * fixes web console introduction and addresses  linking issues
    
    * fix merge conflict
---
 docs/ingestion/data-formats.md       | 2 +-
 docs/operations/druid-console.md     | 2 +-
 docs/operations/high-availability.md | 3 +--
 docs/querying/aggregations.md        | 2 +-
 docs/querying/post-aggregations.md   | 3 +--
 docs/querying/sql.md                 | 4 ++--
 docs/querying/using-caching.md       | 2 +-
 7 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/docs/ingestion/data-formats.md b/docs/ingestion/data-formats.md
index df0f165..2f07d5c 100644
--- a/docs/ingestion/data-formats.md
+++ b/docs/ingestion/data-formats.md
@@ -661,7 +661,7 @@ the set of ingested dimensions, if missing the discovered 
fields will make up th
 
 `timeAndDims` parse spec must specify which fields will be extracted as 
dimensions through the `dimensionSpec`.
 
-[All column types](https://orc.apache.org/docs/types.md) are supported, with 
the exception of `union` types. Columns of
+[All column types](https://orc.apache.org/docs/types.html) are supported, with 
the exception of `union` types. Columns of
  `list` type, if filled with primitives, may be used as a multi-value 
dimension, or specific elements can be extracted with
 `flattenSpec` expressions. Likewise, primitive fields may be extracted from 
`map` and `struct` types in the same manner.
 Auto field discovery will automatically create a string dimension for every 
(non-timestamp) primitive or `list` of
diff --git a/docs/operations/druid-console.md b/docs/operations/druid-console.md
index 8d965c7..3c3ac77 100644
--- a/docs/operations/druid-console.md
+++ b/docs/operations/druid-console.md
@@ -22,7 +22,7 @@ title: "Web console"
   ~ under the License.
   -->
 
-Druid include a console for managing datasources, segments, tasks, data 
processes (Historicals and MiddleManagers), and coordinator dynamic 
configuration. Users can also run SQL and native Druid queries in the console.
+Druid includes a console for managing datasources, segments, tasks, data 
processes (Historicals and MiddleManagers), and coordinator dynamic 
configuration. You can also run SQL and native Druid queries in the console.
 
 The Druid Console is hosted by the [Router](../design/router.md) process.
 
diff --git a/docs/operations/high-availability.md 
b/docs/operations/high-availability.md
index 4e8927f..7d14262 100644
--- a/docs/operations/high-availability.md
+++ b/docs/operations/high-availability.md
@@ -29,8 +29,7 @@ Apache ZooKeeper, metadata store, the coordinator, the 
overlord, and brokers are
 We recommend either installing ZooKeeper on its own hardware, or running 3 or 
5 Master servers (where overlords or coordinators are running)
 and configuring ZooKeeper on them appropriately. See the [ZooKeeper admin 
guide](https://zookeeper.apache.org/doc/current/zookeeperAdmin) for more 
details.
 - For highly-available metadata storage, we recommend MySQL or PostgreSQL with 
replication and failover enabled.
-See [MySQL HA/Scalability 
Guide](https://dev.mysql.com/doc/mysql-ha-scalability/en/)
-and [PostgreSQL's High Availability, Load Balancing, and 
Replication](https://www.postgresql.org/docs/current/high-availability.html) 
for MySQL and PostgreSQL, respectively.
+See [MySQL Enterprise High 
Availability](https://www.mysql.com/products/enterprise/high_availability.html) 
and [PostgreSQL's High Availability, Load Balancing, and 
Replication](https://www.postgresql.org/docs/current/high-availability.html) 
for more information.
 - For highly-available Apache Druid Coordinators and Overlords, we recommend 
to run multiple servers.
 If they are all configured to use the same ZooKeeper cluster and metadata 
storage,
 then they will automatically failover between each other as necessary.
diff --git a/docs/querying/aggregations.md b/docs/querying/aggregations.md
index fe3edc0..f5cf05d 100644
--- a/docs/querying/aggregations.md
+++ b/docs/querying/aggregations.md
@@ -126,7 +126,7 @@ Computes and stores the sum of values as 32-bit floating 
point value. Similar to
 
 ### `doubleMean` aggregator
 
-Computes and returns arithmetic mean of a column values as 64 bit float value. 
`doubleMean` is a query time aggregator only. It is not available for indexing.
+Computes and returns the arithmetic mean of a column's values as a 64-bit 
floating point value. `doubleMean` is a query time aggregator only. It is not 
available for indexing.
 
 To accomplish mean aggregation on ingestion, refer to the [Quantiles 
aggregator](../development/extensions-core/datasketches-quantiles.md#aggregator)
 from the DataSketches extension.
 
diff --git a/docs/querying/post-aggregations.md 
b/docs/querying/post-aggregations.md
index 765aea8..2031309 100644
--- a/docs/querying/post-aggregations.md
+++ b/docs/querying/post-aggregations.md
@@ -96,8 +96,7 @@ The constant post-aggregator always returns the specified 
value.
 
 The difference between the `doubleMax` aggregator and the `doubleGreatest` 
post-aggregator is that `doubleMax` returns the highest value of
 all rows for one specific column while `doubleGreatest` returns the highest 
value of multiple columns in one row. These are similar to the
-SQL 
[MAX](https://dev.mysql.com/doc/refman/5.7/en/group-by-functions.html#function_max)
 and
-[GREATEST](https://dev.mysql.com/doc/refman/5.7/en/comparison-operators.html#function_greatest)
 functions.
+SQL `MAX` and `GREATEST` functions.
 
 Example:
 
diff --git a/docs/querying/sql.md b/docs/querying/sql.md
index 371832c..228420a 100644
--- a/docs/querying/sql.md
+++ b/docs/querying/sql.md
@@ -334,8 +334,8 @@ Only the COUNT, ARRAY_AGG, and STRING_AGG aggregations can 
accept the DISTINCT k
 |`MAX(expr)`|Takes the maximum of numbers.|`null` if 
`druid.generic.useDefaultValueForNull=false`, otherwise `-9223372036854775808` 
(minimum LONG value)|
 |`AVG(expr)`|Averages numbers.|`null` if 
`druid.generic.useDefaultValueForNull=false`, otherwise `0`|
 |`APPROX_COUNT_DISTINCT(expr)`|_Usage note:_ consider using 
`APPROX_COUNT_DISTINCT_DS_HLL` instead, which offers better accuracy in many 
cases.<br/><br/>Counts distinct values of expr, which can be a regular column 
or a hyperUnique column. This is always approximate, regardless of the value of 
"useApproximateCountDistinct". This uses Druid's built-in "cardinality" or 
"hyperUnique" aggregators. See also `COUNT(DISTINCT expr)`.|`0`|
-|`APPROX_COUNT_DISTINCT_DS_HLL(expr, [lgK, tgtHllType])`|Counts distinct 
values of `expr`, which can be a regular column or an [HLL 
sketch](../development/extensions-core/datasketches-hll.md) column. Results are 
always approximate, regardless of the value of 
[`useApproximateCountDistinct`](../querying/sql.html#connection-context). The 
`lgK` and `tgtHllType` parameters here are, like the equivalents in the 
[aggregator](../development/extensions-core/datasketches-hll.html#aggregators), 
des [...]
-|`APPROX_COUNT_DISTINCT_DS_THETA(expr, [size])`|Counts distinct values of 
expr, which can be a regular column or a [Theta 
sketch](../development/extensions-core/datasketches-theta.md) column. This is 
always approximate, regardless of the value of 
[`useApproximateCountDistinct`](../querying/sql.html#connection-context).  The 
`size` parameter is described in the Theta sketch documentation. The 
[DataSketches 
extension](../development/extensions-core/datasketches-extension.md) must be 
loaded [...]
+|`APPROX_COUNT_DISTINCT_DS_HLL(expr, [lgK, tgtHllType])`|Counts distinct 
values of `expr`, which can be a regular column or an [HLL 
sketch](../development/extensions-core/datasketches-hll.md) column. Results are 
always approximate, regardless of the value of 
[`useApproximateCountDistinct`](#connection-context). The `lgK` and 
`tgtHllType` parameters here are, like the equivalents in the 
[aggregator](../development/extensions-core/datasketches-hll.md#aggregators), 
described in the HLL sket [...]
+|`APPROX_COUNT_DISTINCT_DS_THETA(expr, [size])`|Counts distinct values of 
expr, which can be a regular column or a [Theta 
sketch](../development/extensions-core/datasketches-theta.md) column. This is 
always approximate, regardless of the value of 
[`useApproximateCountDistinct`](#connection-context).  The `size` parameter is 
described in the Theta sketch documentation. The [DataSketches 
extension](../development/extensions-core/datasketches-extension.md) must be 
loaded to use this functio [...]
 |`DS_HLL(expr, [lgK, tgtHllType])`|Creates an [HLL 
sketch](../development/extensions-core/datasketches-hll.md) on the values of 
expr, which can be a regular column or a column containing HLL sketches. The 
`lgK` and `tgtHllType` parameters are described in the HLL sketch 
documentation. The [DataSketches 
extension](../development/extensions-core/datasketches-extension.md) must be 
loaded to use this function.|`'0'` (STRING)|
 |`DS_THETA(expr, [size])`|Creates a [Theta 
sketch](../development/extensions-core/datasketches-theta.md) on the values of 
expr, which can be a regular column or a column containing Theta sketches. The 
`size` parameter is described in the Theta sketch documentation. The 
[DataSketches 
extension](../development/extensions-core/datasketches-extension.md) must be 
loaded to use this function.|`'0.0'` (STRING)|
 |`APPROX_QUANTILE(expr, probability, [resolution])`|_Deprecated._ Use 
`APPROX_QUANTILE_DS` instead, which provides a superior 
distribution-independent algorithm with formal error 
guarantees.<br/><br/>Computes approximate quantiles on numeric or 
[approxHistogram](../development/extensions-core/approximate-histograms.md#approximate-histogram-aggregator)
 exprs. The "probability" should be between 0 and 1 (exclusive). The 
"resolution" is the number of centroids to use for the computation. Hi [...]
diff --git a/docs/querying/using-caching.md b/docs/querying/using-caching.md
index e72f4f7..8f85b04 100644
--- a/docs/querying/using-caching.md
+++ b/docs/querying/using-caching.md
@@ -51,7 +51,7 @@ druid.realtime.cache.useCache=true
 druid.realtime.cache.populateCache=true
 ```
 
-See [Peon caching](configuration/index.md#peon-caching) and [Indexer 
caching](configuration/index.md#indexer-caching) for a description of all 
available task executor service caching options.
+See [Peon caching](../configuration/index.md#peon-caching) and [Indexer 
caching](../configuration/index.md#indexer-caching) for a description of all 
available task executor service caching options.
 
 ## Enabling query caching on Brokers
 Brokers support both segment-level and whole-query result level caching.

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