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[SPARK-46188][Doc] Fix the CSS of Spark doc's generated tables #44096

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6effcd7
update CSS
gengliangwang Nov 30, 2023
51f4569
remove class table-striped
gengliangwang Nov 30, 2023
b19c925
revise style
gengliangwang Nov 30, 2023
0fd14ff
Revert "revise style"
gengliangwang Nov 30, 2023
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2 changes: 1 addition & 1 deletion docs/building-spark.md
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Expand Up @@ -284,7 +284,7 @@ If use an individual repository or a repository on GitHub Enterprise, export bel

### Related environment variables

<table class="table table-striped">
<table>
<thead><tr><th>Variable Name</th><th>Default</th><th>Meaning</th></tr></thead>
<tr>
<td><code>SPARK_PROJECT_URL</code></td>
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2 changes: 1 addition & 1 deletion docs/cluster-overview.md
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Expand Up @@ -89,7 +89,7 @@ The [job scheduling overview](job-scheduling.html) describes this in more detail

The following table summarizes terms you'll see used to refer to cluster concepts:

<table class="table table-striped">
<table>
<thead>
<tr><th style="width: 130px;">Term</th><th>Meaning</th></tr>
</thead>
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38 changes: 19 additions & 19 deletions docs/configuration.md
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Expand Up @@ -135,7 +135,7 @@ of the most common options to set are:

### Application Properties

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.app.name</code></td>
Expand Down Expand Up @@ -528,7 +528,7 @@ Apart from these, the following properties are also available, and may be useful

### Runtime Environment

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.driver.extraClassPath</code></td>
Expand Down Expand Up @@ -915,7 +915,7 @@ Apart from these, the following properties are also available, and may be useful

### Shuffle Behavior

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.reducer.maxSizeInFlight</code></td>
Expand Down Expand Up @@ -1290,7 +1290,7 @@ Apart from these, the following properties are also available, and may be useful

### Spark UI

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.eventLog.logBlockUpdates.enabled</code></td>
Expand Down Expand Up @@ -1682,7 +1682,7 @@ Apart from these, the following properties are also available, and may be useful

### Compression and Serialization

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.broadcast.compress</code></td>
Expand Down Expand Up @@ -1880,7 +1880,7 @@ Apart from these, the following properties are also available, and may be useful

### Memory Management

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.memory.fraction</code></td>
Expand Down Expand Up @@ -2005,7 +2005,7 @@ Apart from these, the following properties are also available, and may be useful

### Execution Behavior

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.broadcast.blockSize</code></td>
Expand Down Expand Up @@ -2250,7 +2250,7 @@ Apart from these, the following properties are also available, and may be useful

### Executor Metrics

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.eventLog.logStageExecutorMetrics</code></td>
Expand Down Expand Up @@ -2318,7 +2318,7 @@ Apart from these, the following properties are also available, and may be useful

### Networking

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.rpc.message.maxSize</code></td>
Expand Down Expand Up @@ -2481,7 +2481,7 @@ Apart from these, the following properties are also available, and may be useful

### Scheduling

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.cores.max</code></td>
Expand Down Expand Up @@ -2962,7 +2962,7 @@ Apart from these, the following properties are also available, and may be useful

### Barrier Execution Mode

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.barrier.sync.timeout</code></td>
Expand Down Expand Up @@ -3009,7 +3009,7 @@ Apart from these, the following properties are also available, and may be useful

### Dynamic Allocation

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.dynamicAllocation.enabled</code></td>
Expand Down Expand Up @@ -3151,7 +3151,7 @@ finer granularity starting from driver and executor. Take RPC module as example
like shuffle, just replace "rpc" with "shuffle" in the property names except
<code>spark.{driver|executor}.rpc.netty.dispatcher.numThreads</code>, which is only for RPC module.

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.{driver|executor}.rpc.io.serverThreads</code></td>
Expand Down Expand Up @@ -3294,7 +3294,7 @@ External users can query the static sql config values via `SparkSession.conf` or

### Spark Streaming

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.streaming.backpressure.enabled</code></td>
Expand Down Expand Up @@ -3426,7 +3426,7 @@ External users can query the static sql config values via `SparkSession.conf` or

### SparkR

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.r.numRBackendThreads</code></td>
Expand Down Expand Up @@ -3482,7 +3482,7 @@ External users can query the static sql config values via `SparkSession.conf` or

### GraphX

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.graphx.pregel.checkpointInterval</code></td>
Expand Down Expand Up @@ -3519,7 +3519,7 @@ copy `conf/spark-env.sh.template` to create it. Make sure you make the copy exec
The following variables can be set in `spark-env.sh`:


<table class="table table-striped">
<table>
<thead><tr><th style="width:21%">Environment Variable</th><th>Meaning</th></tr></thead>
<tr>
<td><code>JAVA_HOME</code></td>
Expand Down Expand Up @@ -3656,7 +3656,7 @@ Push-based shuffle helps improve the reliability and performance of spark shuffl

### External Shuffle service(server) side configuration options

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.shuffle.push.server.mergedShuffleFileManagerImpl</code></td>
Expand Down Expand Up @@ -3690,7 +3690,7 @@ Push-based shuffle helps improve the reliability and performance of spark shuffl

### Client side configuration options

<table class="table table-striped">
<table>
<thead><tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since Version</th></tr></thead>
<tr>
<td><code>spark.shuffle.push.enabled</code></td>
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13 changes: 13 additions & 0 deletions docs/css/custom.css
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Expand Up @@ -1111,5 +1111,18 @@ img {
table {
width: 100%;
overflow-wrap: normal;
border-collapse: collapse; /* Ensures that the borders collapse into a single border */
}

table th, table td {
border: 1px solid #cccccc; /* Adds a border to each table header and data cell */
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@gengliangwang gengliangwang Nov 30, 2023

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I asked ChatGPT to recover the CSS with doc. It looks good so I keep it.

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@gengliangwang gengliangwang Nov 30, 2023

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The result of the changes are done by myself.

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@grundprinzip grundprinzip Nov 30, 2023

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why dropping the striped this is exactly what the bootstrap theme already provides us.

The easier way would be simply to

.table {
  border-collapse: collapse;
  border: 1px solid #ccc
}

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@gengliangwang gengliangwang Nov 30, 2023

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I tried the striped style but it was not very clear when there is long text ( you can find it in the commit history):
image

padding: 6px 13px; /* Optional: Adds padding inside each cell for better readability */
}

table tr {
background-color: white; /* Sets a default background color for all rows */
}

table tr:nth-child(2n) {
background-color: #F1F4F5; /* Sets a different background color for even rows */
}
14 changes: 7 additions & 7 deletions docs/ml-classification-regression.md
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Expand Up @@ -703,7 +703,7 @@ others.

### Available families

<table class="table table-striped">
<table>
<thead>
<tr>
<th>Family</th>
Expand Down Expand Up @@ -1224,7 +1224,7 @@ All output columns are optional; to exclude an output column, set its correspond

### Input Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand All @@ -1251,7 +1251,7 @@ All output columns are optional; to exclude an output column, set its correspond

### Output Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand Down Expand Up @@ -1326,7 +1326,7 @@ All output columns are optional; to exclude an output column, set its correspond

#### Input Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand All @@ -1353,7 +1353,7 @@ All output columns are optional; to exclude an output column, set its correspond

#### Output Columns (Predictions)

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand Down Expand Up @@ -1407,7 +1407,7 @@ All output columns are optional; to exclude an output column, set its correspond

#### Input Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand Down Expand Up @@ -1436,7 +1436,7 @@ Note that `GBTClassifier` currently only supports binary labels.

#### Output Columns (Predictions)

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand Down
8 changes: 4 additions & 4 deletions docs/ml-clustering.md
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Expand Up @@ -40,7 +40,7 @@ called [kmeans||](http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf).

### Input Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand All @@ -61,7 +61,7 @@ called [kmeans||](http://theory.stanford.edu/~sergei/papers/vldb12-kmpar.pdf).

### Output Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand Down Expand Up @@ -204,7 +204,7 @@ model.

### Input Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand All @@ -225,7 +225,7 @@ model.

### Output Columns

<table class="table table-striped">
<table>
<thead>
<tr>
<th align="left">Param name</th>
Expand Down
2 changes: 1 addition & 1 deletion docs/mllib-classification-regression.md
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Expand Up @@ -26,7 +26,7 @@ classification](http://en.wikipedia.org/wiki/Multiclass_classification), and
[regression analysis](http://en.wikipedia.org/wiki/Regression_analysis). The table below outlines
the supported algorithms for each type of problem.

<table class="table table-striped">
<table>
<thead>
<tr><th>Problem Type</th><th>Supported Methods</th></tr>
</thead>
Expand Down
2 changes: 1 addition & 1 deletion docs/mllib-decision-tree.md
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Expand Up @@ -51,7 +51,7 @@ The *node impurity* is a measure of the homogeneity of the labels at the node. T
implementation provides two impurity measures for classification (Gini impurity and entropy) and one
impurity measure for regression (variance).

<table class="table table-striped">
<table>
<thead>
<tr><th>Impurity</th><th>Task</th><th>Formula</th><th>Description</th></tr>
</thead>
Expand Down
2 changes: 1 addition & 1 deletion docs/mllib-ensembles.md
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Expand Up @@ -191,7 +191,7 @@ Note that each loss is applicable to one of classification or regression, not bo

Notation: $N$ = number of instances. $y_i$ = label of instance $i$. $x_i$ = features of instance $i$. $F(x_i)$ = model's predicted label for instance $i$.

<table class="table table-striped">
<table>
<thead>
<tr><th>Loss</th><th>Task</th><th>Formula</th><th>Description</th></tr>
</thead>
Expand Down
10 changes: 5 additions & 5 deletions docs/mllib-evaluation-metrics.md
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Expand Up @@ -76,7 +76,7 @@ plots (recall, false positive rate) points.

**Available metrics**

<table class="table table-striped">
<table>
<thead>
<tr><th>Metric</th><th>Definition</th></tr>
</thead>
Expand Down Expand Up @@ -179,7 +179,7 @@ For this section, a modified delta function $\hat{\delta}(x)$ will prove useful

$$\hat{\delta}(x) = \begin{cases}1 & \text{if $x = 0$}, \\ 0 & \text{otherwise}.\end{cases}$$

<table class="table table-striped">
<table>
<thead>
<tr><th>Metric</th><th>Definition</th></tr>
</thead>
Expand Down Expand Up @@ -296,7 +296,7 @@ The following definition of indicator function $I_A(x)$ on a set $A$ will be nec

$$I_A(x) = \begin{cases}1 & \text{if $x \in A$}, \\ 0 & \text{otherwise}.\end{cases}$$

<table class="table table-striped">
<table>
<thead>
<tr><th>Metric</th><th>Definition</th></tr>
</thead>
Expand Down Expand Up @@ -447,7 +447,7 @@ documents, returns a relevance score for the recommended document.

$$rel_D(r) = \begin{cases}1 & \text{if $r \in D$}, \\ 0 & \text{otherwise}.\end{cases}$$

<table class="table table-striped">
<table>
<thead>
<tr><th>Metric</th><th>Definition</th><th>Notes</th></tr>
</thead>
Expand Down Expand Up @@ -553,7 +553,7 @@ variable from a number of independent variables.

**Available metrics**

<table class="table table-striped">
<table>
<thead>
<tr><th>Metric</th><th>Definition</th></tr>
</thead>
Expand Down
4 changes: 2 additions & 2 deletions docs/mllib-linear-methods.md
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Expand Up @@ -72,7 +72,7 @@ training error) and minimizing model complexity (i.e., to avoid overfitting).
The following table summarizes the loss functions and their gradients or sub-gradients for the
methods `spark.mllib` supports:

<table class="table table-striped">
<table>
<thead>
<tr><th></th><th>loss function $L(\wv; \x, y)$</th><th>gradient or sub-gradient</th></tr>
</thead>
Expand Down Expand Up @@ -105,7 +105,7 @@ The purpose of the
encourage simple models and avoid overfitting. We support the following
regularizers in `spark.mllib`:

<table class="table table-striped">
<table>
<thead>
<tr><th></th><th>regularizer $R(\wv)$</th><th>gradient or sub-gradient</th></tr>
</thead>
Expand Down
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