CASSANDRA-21291: Fix duplicate section and minor formatting typos in compaction overview

Author: arvindKandpal-ksolves

doc/modules/cassandra/pages/managing/operating/compaction/overview.adoc

@@ -2,18 +2,18 @@
 
 == What is compaction?
 
-Data in {cassandra} is created in xref:cassandra:architecture/storage-engine.adoc#memtables[memtables]. 
+Data in {cassandra} is created in xref:cassandra:architecture/storage-engine.adoc#memtables[memtables]. 
 Once a memory threshold is reached, to free up memory again, the data is written to an xref:cassandra:architecture/storage-engine.adoc#SSTables[SSTable], an https://cassandra.apache.org/_/glossary.html#immutable[immutable] file residing on disk.
 
-Because SSTables are immutable, when data is updated or deleted, the old data is not overwritten with inserts or updates, or removed from the SSTable. 
-Instead, a new SSTable is created with the updated data with a new timestamp, and the old SSTable is marked for deletion. 
+Because SSTables are immutable, when data is updated or deleted, the old data is not overwritten with inserts or updates, or removed from the SSTable. 
+Instead, a new SSTable is created with the updated data with a new timestamp, and the old SSTable is marked for deletion. 
 The piece of deleted data is known as a https://cassandra.apache.org/_/glossary.html#tombstone[tombstone].
 
-Over time, Cassandra may write many versions of a row in different SSTables. 
-Each version may have a unique set of columns stored with a different timestamp. 
+Over time, Cassandra may write many versions of a row in different SSTables. 
+Each version may have a unique set of columns stored with a different timestamp. 
 As SSTables accumulate, the distribution of data can require accessing more and more SSTables to retrieve a complete row.
 
-To keep the database healthy, Cassandra periodically merges SSTables and discards old data. 
+To keep the database healthy, Cassandra periodically merges SSTables and discards old data. 
 This process is called https://cassandra.apache.org/_/glossary.html#compaction[compaction].
 
 == Why must compaction be run?
@@ -26,22 +26,22 @@ Deleting, updating, or expiring data are all valid triggers for compaction.
 == What does compaction accomplish?
 
 Two important factors accomplished by compaction are performance improvement and disk space reclamation.
-If SSTables have duplicate data that must be read, read operations are slower. 
+If SSTables have duplicate data that must be read, read operations are slower. 
 Once tombstones and duplicates are removed, read operations are faster.
 SSTables use disk space, and reducing the size of SSTables through compaction frees up disk space.
 
 == How does compaction work?
 
-Compaction works on a collection of SSTables. 
-From these SSTables, compaction collects all versions of each unique row and assembles one complete row, using the most up-to-date version (by timestamp) of each of the row's columns. 
-The merge process is performant, because rows are sorted by partition key within each SSTable, and the merge process does not use random I/O. 
-The new versions of each row is written to a new SSTable. 
+Compaction works on a collection of SSTables. 
+From these SSTables, compaction collects all versions of each unique row and assembles one complete row, using the most up-to-date version (by timestamp) of each of the row's columns. 
+The merge process is performant, because rows are sorted by partition key within each SSTable, and the merge process does not use random I/O. 
+The new versions of each row is written to a new SSTable. 
 The old versions, along with any rows that are ready for deletion, are left in the old SSTables, and are deleted as soon as pending reads are completed.
 
 == Types of compaction
 
 The concept of compaction is used for different kinds of operations in
-{cassandra}, the common thing about these operations is that it takes one
+{cassandra}, the common thing about these operations is that they take one
 or more SSTables, merges, and outputs new SSTables. The types of compactions are:
 
 Minor compaction::
@@ -56,11 +56,11 @@ A major compaction is triggered when a user executes a compaction over all SSTab
 User defined compaction::
 Similar to a major compaction, a user-defined compaction executes when a user triggers a compaction on a given set of SSTables.
 Scrub::
-A scrub triggers a compaction to try to fix any broken SSTables. 
+A scrub triggers a compaction to try to fix any broken SSTables. 
 This can actually remove valid data if that data is corrupted.
 If that happens you will need to run a full repair on the node.
 UpgradeSSTables::
-A compaction occurs when you upgrade SSTables to the latest version. 
+A compaction occurs when you upgrade SSTables to the latest version. 
 Run this after upgrading to a new major version.
 Cleanup::
 Compaction executes to remove any ranges that a node no longer owns.
@@ -71,8 +71,8 @@ Anticompaction::
 After repair, the ranges that were actually repaired are split out of the SSTables that existed when repair started. This type of compaction rewrites SSTables to accomplish this task.
 Sub range compaction::
 It is possible to only compact a given sub range - this action is useful if you know a token that has been misbehaving - either gathering many updates or many deletes.
-The command `nodetool compact -st x -et y` will pick all SSTables containing the range between x and y and issue a compaction for those SSTables. 
-For Size Tiered Compaction Strategy, this will most likely include all SSTables, but with Leveled Compaction Strategy, it can issue the compaction for a subset of the SSTables. 
+The command `nodetool compact -st x -et y` will pick all SSTables containing the range between x and y and issue a compaction for those SSTables. 
+For Size Tiered Compaction Strategy, this will most likely include all SSTables, but with Leveled Compaction Strategy, it can issue the compaction for a subset of the SSTables. 
 With LCS the resulting SSTable will end up in L0.
 
 == Strategies
@@ -82,14 +82,14 @@ Picking the right compaction strategy for your workload will ensure the best per
 
 xref:cassandra:managing/operating/compaction/ucs.adoc[`Unified Compaction Strategy (UCS)`]::
 UCS is a good choice for most workloads and is recommended for new workloads.
-This compaction strategy is designed to handle a wide variety of workloads. 
-It is designed to be able to handle both immutable time-series data and workloads with lots of updates and deletes. 
-It is also designed to be able to handle both spinning disks and SSDs.  
-xref:cassandra:managing/operating/compaction/stcs.adoc[`Size Tiered Compaction Strategy (STCS)`]:: 
-STCS is the default compaction strategy, because it is useful as a fallback when other strategies don't fit the workload. 
+This compaction strategy is designed to handle a wide variety of workloads. 
+It is designed to be able to handle both immutable time-series data and workloads with lots of updates and deletes. 
+It is also designed to be able to handle both spinning disks and SSDs.  
+xref:cassandra:managing/operating/compaction/stcs.adoc[`Size Tiered Compaction Strategy (STCS)`]:: 
+STCS is the default compaction strategy, because it is useful as a fallback when other strategies don't fit the workload. 
 Most useful for not strictly time-series workloads with spinning disks, or when the I/O from `LCS` is too high.
 xref:cassandra:managing/operating/compaction/lcs.adoc[`Leveled Compaction Strategy (LCS)`]::
-Leveled Compaction Strategy (LCS) is optimized for read heavy workloads, or workloads with lots of updates and deletes. 
+Leveled Compaction Strategy (LCS) is optimized for read heavy workloads, or workloads with lots of updates and deletes. 
 It is not a good choice for immutable time-series data.
 xref:cassandra:managing/operating/compaction/twcs.adoc[`Time Window Compaction Strategy (TWCS)`]::
 Time Window Compaction Strategy is designed for TTL'ed, mostly immutable time-series data.
@@ -107,19 +107,6 @@ of the TTL) Cassandra will have a hard time dropping the tombstones
 created since the partition might span many SSTables and not all are
 compacted at once.
 
-== Fully expired SSTables
-
-If an SSTable contains only tombstones and it is guaranteed that
-SSTable is not shadowing data in any other SSTable, then the compaction can drop
-that SSTable. If you see SSTables with only tombstones (note that TTL-ed
-data is considered tombstones once the time-to-live has expired), but it
-is not being dropped by compaction, it is likely that other SSTables
-contain older data. There is a tool called `sstableexpiredblockers` that
-will list which SSTables are droppable and which are blocking them from
-being dropped. With `TimeWindowCompactionStrategy` it
-is possible to remove the guarantee (not check for shadowing data) by
-enabling `unsafe_aggressive_sstable_expiration`.
-
 == Repaired/unrepaired data
 
 With incremental repairs Cassandra must keep track of what data is
@@ -161,8 +148,8 @@ When an SSTable is written a histogram with the tombstone expiry times
 is created and this is used to try to find SSTables with very many
 tombstones and run single SSTable compaction on that SSTable in hope of
 being able to drop tombstones in that SSTable. Before starting this it
-is also checked how likely it is that any tombstones will actually will
-be able to be dropped how much this SSTable overlaps with other
+is also checked how likely it is that any tombstones will actually
+be able to be dropped and how much this SSTable overlaps with other
 SSTables. To avoid most of these checks the compaction option
 `unchecked_tombstone_compaction` can be enabled.
 
@@ -178,11 +165,11 @@ How much of the SSTable should be tombstones for us to consider doing a single S
 `tombstone_compaction_interval` (default: 86400s (1 day))::
 Since it might not be possible to drop any tombstones when doing a single SSTable compaction we need to make sure that one SSTable is not constantly getting recompacted - this option states how often we should try for a given SSTable.
 `log_all` (default: false)::
-New detailed compaction logging, see `below <detailed-compaction-logging>`.
+New detailed compaction logging, see <<detailed-compaction-logging, below>>.
 `unchecked_tombstone_compaction` (default: false)::
-The single SSTable compaction has quite strict checks for whether it should be started, this option disables those checks and for some use cases this might be needed. 
+The single SSTable compaction has quite strict checks for whether it should be started, this option disables those checks and for some use cases this might be needed. 
 Note that this does not change anything for the actual compaction, tombstones are only dropped if it is safe to do so - it might just rewrite an SSTable without being able to drop any tombstones.
-`only_purge_repaired_tombstone` (default: false)::
+`only_purge_repaired_tombstones` (default: false)::
 Option to enable the extra safety of making sure that tombstones are only dropped if the data has been repaired.
 `min_threshold` (default: 4)::
 Lower limit of number of SSTables before a compaction is triggered.
@@ -195,7 +182,7 @@ Further, see the section on each strategy for specific additional options.
 
 == Compaction nodetool commands
 
-The `nodetool <nodetool>` utility provides a number of commands related to compaction:
+The `nodetool` utility provides a number of commands related to compaction:
 
 `enableautocompaction`::
 Enable compaction.
@@ -212,7 +199,7 @@ Set the min/max SSTable count for when to trigger compaction, defaults to 4/32.
 
 == Switching the compaction strategy and options using JMX
 
-It is possible to switch compaction strategies and its options on just a single node using JMX, this is a great way to experiment with settings without affecting the whole cluster. 
+It is possible to switch compaction strategies and its options on just a single node using JMX, this is a great way to experiment with settings without affecting the whole cluster. 
 The mbean is:
 
 [source,console]

doc/modules/cassandra/pages/managing/operating/compaction/tombstones.adoc

@@ -69,22 +69,21 @@ This is basically the same as in the "Deletes without Tombstones" section.
 
 === Deletes without tombstones
 
-Imagine a three node cluster which has the value [A] replicated to every
-node.:
+Imagine a three node cluster which has the value [A] replicated to every node:
 
 [source,none]
 ----
 [A], [A], [A]
 ----
 
-If one of the nodes fails and and our delete operation only removes existing values, we can end up with a cluster that looks like:
+If one of the nodes fails and our delete operation only removes existing values, we can end up with a cluster that looks like:
 
 [source,none]
 ----
 [], [], [A]
 ----
 
-Then a repair operation would replace the value of [A] back onto the two nodes which are missing the value.:
+Then a repair operation would replace the value of [A] back onto the two nodes which are missing the value:
 
 [source,none]
 ----
@@ -95,7 +94,7 @@ This would cause our data to be resurrected as a zombie even though it had been
 
 === Deletes with tombstones
 
-Starting again with a three node cluster which has the value [A] replicated to every node.:
+Starting again with a three node cluster which has the value [A] replicated to every node:
 
 [source,none]
 ----